816results about How to "High solution accuracy" patented technology

The invention relates to a vector-relation-based method for calibrating single-line laser radar and a CCD camera. Point set information of the laser radar for scanning a V-shaped target is extracted in a laser coordinate system, and direction vectors and intersection coordinates of straight lines in two different planes of the target are obtained by means of straight line fitting; the CCD camera is used for capturing images in a camera coordinate system, target plane equations and an equation of a plane passing through an original point and laser radar scanning lines are obtained by processing image information, a straight-line equation of laser radar scanning is built, and furthermore, the direction vectors and the intersection coordinates of the straight lines are obtained; finally, calibration is finished according to the relations between direction vectors and the intersection coordinates of the straight lines corresponding to the different coordinate systems. According to the method, no object in a calibration scene needs to be moved, collection of all calibration data can be completed at a time, and calibration efficiency is improved greatly. According to the method, the direction vectors of the straight lines of the laser scanning target planes under the coordinate systems of sensors to be calibrated are obtained directly, calibration precision is guaranteed, and meanwhile the calibration algorithm is simplified.

The invention provides a measuring device and method for the target line-of-sight angel offset and distance. The device is composed of a four-quadrant avalanche photodetector, a receiving and sending optical unit, a noise compensation circuit, a four-circuit front amplification circuit, a video amplification circuit, an automatic gain amplification circuit, a peak keeping circuit, an AD conversion circuit, a laser, a dominant wave sampling circuit, a summing circuit, a time identifying circuit, a time test circuit and a digital processing circuit, wherein the receiving and sending optical unit enables narrow pulse laser rays emitted by the laser to be converged on the photoelectric detector to form echo light spots after target reflection, photovoltaic conversion of the four-quadrant avalanche photodetector, front amplification, video amplification and automatic gain amplification are conducted, narrow-pulse peak keeping is conducted, transmission of the AD conversion circuit is conducted, and the digital processing circuit extracts the digital line-of-sight angel offset; summing is conducted on the four-circuit front amplification circuit, the dominant wave sampling circuit is combined, the time identifying circuit determines laser emitting and echo coming and returning time, the time is transmitted to the time identifying circuit to be measured, and the digital processing circuit decodes the corresponding distance.

The invention discloses a method and system for multi-target reactive power optimization of electric power systems. The method comprises the following steps of: establishing a multi-target reactive power optimization model; generating positions of N initial bird nests by utilizing Kent chaotic mapping, taking the positions of the N bird nests as initial populations, calculating a fitness value of each bird nest, establishing an external file set according to a Pareto dominance relation, updating the positions of the bird nests according to self-adaptive weights, updating the external file set according to the dominance relation and calculating a congestion distance to control the capacity of the file set; carrying out a differential evolution operation on each bird nest and updating the external file set; and when an iteration termination condition is satisfied, outputting an optimum Pareto optimal solution set. According to the method and system, a plurality of target functions are considered, so that the disadvantages that the traditional method is used for converting a plurality of targets into a single target and is difficult to determine the weight coefficients are optimally overcome; an improved cuckoo search algorithm is high in convergence rate, high in precision and good in individual diversity; and the obtained optimal solution set has favorable diversity and uniform distributivity, and can be well adapted to solving the multi-target reactive power optimization problems of the electric power systems.

The invention provides a cooperative air combat firepower distribution method based on an improved multi-target leapfrog algorithm and belongs to the technical field of computer simulation and method optimization. The method comprises the steps that firstly, required data information is obtained through a cooperative air combat formation command and control system; secondly, a multi-target optimization module of cooperative air combat firepower distribution is established; then a multi-target quantum leapfrog algorithm based on a self-adaptive mesh method is carried out, and a Pareto non-inferior solution of firepower distribution problem is solved; finally, rules can be selected independently according to the optimal distribution scheme, and the optimal firepower distribution scheme is selected from the non-inferior solution. The cooperative air combat firepower distribution method based on the improved multi-target leapfrog algorithm has the major functions that weapons on a fighter aircraft on an attack mission are distributed to multiple targets according to the optimal firepower distribution scheme, the formed cooperative air combat is enabled to realize the optimal cooperative attack effect, and the maximum operational effectiveness is obtained.

The invention discloses an RBF neural network optimization algorithm based on an improved sparrow search algorithm. RBF initial parameters are optimized through the improved sparrow search algorithm,so that the sea clutter prediction precision is further improved, and the purpose of suppression is achieved. An elite reverse learning strategy is introduced, a current optimal solution is selected as an elite individual, and a reverse solution of the elite individual is generated, so that the global search capability of the algorithm is enhanced. Self-adaptive Gaussian variation is adopted to perform variation on an optimal solution and perform greedy selection, and in addition, a position updating mode for sparrow investigation early warning is also improved. And the population is promotedto evolve towards the optimal solution direction, so that the problem that sparrows are easy to fall into local optimum in the convergence process of low fitness in the sparrow search algorithm is avoided to a certain extent. The ability of the improved sparrow search algorithm to jump out of the local optimum is enhanced, and the convergence speed and precision of the RBF network optimized by theimproved sparrow search algorithm are further improved.

A latitude unknown self-aligning method of a strapdown inertial navigation system under the dynamic interference condition includes the steps that firstly, a geometrical analytic formula is built by means of the characteristic that the projection of gravity acceleration is unchanged in an inertial coordinate system, the gravity acceleration is subjected to integration to obtain speed information, and the latitude value of the position where a carrier is located is calculated according to the speed information; secondly, on the basis of the double-vector altitude determination principle and by means of the characteristic that the gravity acceleration of an inertial system includes north orientation information, rough solution of an initial attitude matrix under the inertial system is achieved; finally, on the basis that coarse alignment is finished, a precise alignment error model under the latitude unknown dynamic interference condition is built according to a speed error equation, a misalignment angle equation and a latitude error equation, the latitude error angle and the misalignment angle of the carrier are calculated by means of the self-adaptive filtering method based on information, the latitude value is compensated with the latitude error angle, the strapdown altitude matrix is corrected according to the misalignment angle, and high-precision quick self-aligning of the strapdown inertial navigation system is achieved.

The invention discloses an uninhabited combat air vehicle route path determining method based on a PGSO (Particle-Glowworm Swarm Optimization) algorithm. The PGSO algorithm is designed by integrating a particle swarm optimization algorithm and a glowworm swarm optimization algorithm; a high-efficiency PGSO algorithm is designed by simulating a behavioural process of glowworms and establishing a swarm intelligence algorithm model under the inspiration of foraging or companion attracting courtship behaviors of the glowworms in nature through luminescence (fluorescein) and a bird swarm foraging behavior on the basis of a biological principle of a glowworm swarm in the nature; the high-efficiency PGSO algorithm is applied to determining of an uninhabited combat air vehicle route path; the uninhabited combat air vehicle route path determining method which is more excellent in performance is provided; a parallel hybrid mutation strategy and a strategy for performing local search close to the position of a global optimal individual are introduced into the PGSO, so that higher flight speed and positioning accuracy are achieved by finding the uninhabited combat air vehicle route path by utilizing the PGSO.

The invention provides a vehicle-mounted integrated navigation system. The vehicle-mounted integrated navigation system includes an inertial measurement device, a satellite navigation module, an odometer and an integrated navigation computer. The inertial measurement device includes a gyroscope and an accelerometer. The integrated navigation computer is connected with the inertial measurement device, the satellite navigation module and the odometer, and is provided with an inertial navigation subsystem and a Kalman filter. The inertial navigation subsystem performs inertial navigation solutionon an inertial navigation signal to obtain inertial navigation parameters. The Kalman filter can use information provided by the satellite navigation module or a carrier movement speed provided by the odometer as an observation signal in a switch mode to dynamically estimate errors of the inertial navigation parameters, and correct the navigation parameters based on the errors. The vehicle-mounted integrated navigation system adopts a combination of inertial navigation, satellite navigation and the odometer, so that the solution accuracy of inertial navigation can be improved in areas with good satellite navigation signals, and the vehicle-mounted integrated navigation system can still provide high-precision location information for vehicles in areas with reduced satellite navigation positioning accuracy or unavailable satellite navigation positioning.

The invention provides a compensation method for airplane aeromagnetic interference, relates to the field of aeromagnetic detection, and aims at solving the problem that the estimation precision of the compensation coefficient is influenced by the morbid state of a present aeromagnetic interference coefficient calculation method. The method comprises the following steps that 1) a matrix delta is constructed; 2) the matrix delta is decomposed by wavelet; 3) bandbass filtering is carried out on a result of the step 2); 4) a subscript set L is determined so that the morbid state of bpf<L>(delta) is the weakest; and 5) a compensation coefficient equation is determined to solve the compensation coefficient of aeromagnetic interference. The method provided by the invention can effectively reduce the morbid state of the coefficient solution matrix, improve the solution precision of the compensation coefficient estimation algorithm, and can be applied to the field of aeromagnetic detection.

The invention relates to a pedestrian navigation system three-dimensional spatial positioning method based on human / environment constraints and solves the problem with high-precision positioning of a pedestrian navigation system in a three-dimensional space, wherein the system is designed based on a low-cost MEMS (micro-electromechanical system) inertial measurement unit; data collection and strap-down navigation calculation are performed by installing the MEMS inertial measurement unit on a shoe, and zero-speed ranges in pedestrian gaits are detected in connection with data output by a pressure sensor installed on a sole. A scheme is provided based on zero speed correction in connection with pedestrian motion characteristics and ambient building characteristics, the scheme is about constraining magnetic field abnormality in zero-speed ranges and constraining SINS (ship's inertial navigation system) height channel divergence, and an extended Kalman filter is designed to correct errors in navigation calculation results, thereby enabling high-precision positioning of pedestrians in the three-dimensional space.

The invention discloses a flexible job shop batch dynamic scheduling optimization method. According to the method, a production mode of batch scheduling and the dynamic factor of machine malfunction are introduced into a flexible job shop scheduling problem; relevant constraints are extended as needed with delivery period constraints considered, a BDFJSP problem model adopting minimizing delay time as an objective is established; on the basis of the problem model, a Q learning mode is adopted to train an agent, so that a solution can be obtained, and a reasonable state set, an action set and areward function are established according to the problem; and in order to better balance exploration and utilization in the Q learning, epsilon greedy search is integrated into the Q learning, and areasonable epsilon attenuation function is set. The method is of great significance and engineering practical application value for solving the job scheduling of flexible shops and even discrete optimization problems similar to the job scheduling of the flexible shops.

The invention relates to a device and a method of the detection of a laser-beam deflection angle by a full digital four quadrant detector, and comprises a preposed amplifying electric circuit (12), a filtering electric circuit(13), an AD switching electric circuit(16), an offset display module(18), a four quadrant detector(1), a secondary amplifying electric circuit module(14), a variable gain amplifying electric circuit module(15) and a high speed micro processor module(17). The invention solves the problem of reduced measurement precision by using a full digital processing method; the model adopts the auto adaptation and the variable gain amplifying electric circuit to maintain the strength of signals entering an AD collecting unit by the automatic variation of the gain according to strengths of input signals; the model overcomes a reduced resolving precision caused by a reduced signal to noise ratio resulting from the variation of input light intensity. The invention overcomes the defect of a slow resolving speed caused by using a single chip for resolving by using the high speed micro processor to resolve the beam reflection angles.

The invention provides a satellite clock error real-time estimation method based on area multi-reference-station joint resolving. The precision and timeliness of real-time precise single point positioning is improved. The method is based on a satellite and epoch difference technology, GNSS carrier phase observed values collected by area reference stations in real time and an IGU ephemeris provided by an international GNSS IGS center are utilized, the relative satellite clock error relative to a reference epoch is obtained through the multi-reference-station joint resolving , and the relative lock error values of all the epochs are obtained with the IGU precast clock error and interpolated values in the IGU precast clock error. According to the method, the operating quantity is small, the resolving speed is high, and a high-precision real-time satellite clock error product can be obtained fast through a small number of reference station carrier phase observed values. The method is based on the multi-reference-station GNSS data joint processing, the instability of single base station resolving is avoided, and the negative influence on the clock error estimation by convection zone parameter time and space correlation is reduced.

The invention relates to a mechanical arm tail-end pose error correction method based on elliptic characteristics. The method comprises the steps of obtaining an image of a round-mouth target tank, extracting a target ellipse from the image, determining the relative position and axial relation between a tank mouth of the round-mouth target tank and an actuator according to the elliptic characteristics of the target ellipse, determining a current pose of the actuator, joint angles of all joints of a mechanical arm and the pose deviation value of the actuator according to the relative positions,the axial relation and configuration constraint of the mechanical arm, and adjusting the mechanical arm according to the pose deviation value till the pose deviation value of the actuator is smallerthan a preset value. By means of the method, the problems that single elliptic characteristic positioning has ambiguity and axial rotation poses cannot be determined are solved, accurate guidance canbe provided for the mechanical arm to collect samples and put the samples into the target tank, and control errors caused by local flexibility or joint clearance are corrected. The invention further provides a mechanical arm tail-end pose error correction system based on the elliptic characteristics.

The invention discloses a bidirectional fluid-solid-heat coupling calculating method of a water-lubricated rubber bearing, comprising the following steps of setting basic assumption of a solution process according to the special structure and practical operating condition of the water-lubricated rubber bearing and combined with heat transfer characteristics of the water-lubricated rubber bearing; determining fluid, solid and temperature field coupling boundary conditions of the water-lubricated rubber bearing; building fluid domain and solid domain solution models, including mathematical models and mechanical models, of the water-lubricated rubber bearing,; meshing the fluid domain and solid domain of the water-lubricated rubber bearing by means of a finite element software platform and professional meshing software; building differential control equations of the fluid domain, solid domain and heat transfer characteristics of the water-lubricated rubber bearing; and building a fluid-solid-heat coupling model of the water-lubricated rubber bearing, solving the fluid-solid-heat coupling model by using a numerical method, and obtaining deformation conditions of the fluid domain, solid domain and temperature field. The method is effectively suitable for three-field coupling solution of the water-lubricated rubber bearing, solution precision is high, and the number of iterations is low.

The invention provides a multi-antenna attitude determining method based on a Beidou system. With the establishment and improvement of the Beidou satellite regional navigation system, the use of the Beidou satellite system for high-precision attitude determination has become one of the hot spots in the field of navigation. The method is based on the realization of the Beidou receiver hardware embedded platform and based on the three-antenna carrier phase data simultaneously observed by the Beidou receiver, the double-difference model is constructed and finally the high-precision attitude information is obtained. The present invention mainly makes innovation and improvement of the satellite selection strategy, the cycle slip detection method, the rough error rejecting and fuzziness calculation method, the base line verification method in the attitude determination flow. The method is highly modularized, supports various platforms, is particularly suitable for the embedded receiver platform, and has a wide application prospect.

The invention relates to a determination method based on an ANSYS second development platform of the initial completion initial cable force of a cable-stayed bridge. The method uses the design cable force as the target value, considers the geometric non-linear effect and performs iteration for solving and correcting the cable initial strain under the action of dead load. The method comprises the following specific steps: any group of cable forces is assumed to be added on the stay cable in the mode of initial strain, dead load is added to calculate, the *do-loop command language is used to extract the calculated cable force of the stay cable and check whether the error between the cable force and the target completion cable force is within an available limit; if the error is large, the indifference method is used to correct the stay cable initial strain, then the error is calculated again until the error is within the available limit; and the initial completion initial cable force can be obtained by multiplying the last calculated group of stay cable initial strains by the elastic modulus of the stay cable which is corrected by considering the vertical effect. By using the method, the solving time of the completion initial cable force of the cable-stayed bridge can be reduced and the precision can be increased, thus the method has large practical engineering application value.

This invention relates to an intelligent airborne missile moving base alignment and calibration method. Based on the time variation property of Strapdown Inertial Navigation System model under the moving base condition, a neural network input and output sample construction method which is adequate for the alignment and calibration of moving base is provided. In order to settle the question that when hanging beneath the aircraft wing, the inertial navigation subsystem measuring information of the missile is not the same as when flying freely, the error angle between inertial navigation system and subsystem is firstly estimated and compensated before neural network training. Thus, the neural network training sample can simulate the freely flying state of missile accurately. This invention can increase the navigating accuracy.

The invention discloses an operator construction method of a single-star scheduling. The operator construction method comprises the following steps that a question classifier which is constructed based on a distribution form of a task set conducts classification on single-star scheduling sub-questions; (2) an ant colony algorithm is constructed; (3) a question operator knowledge base is constructed through question classification, an operator design ruler and a score triple and records the historical performance when each operator design is used for solving each type of questions, and therefore operator design decision support is provided for solution of new concrete questions in the feature. The operator construction method of the single-star scheduling has the advantage that under the condition that solution quality is guaranteed, the solving efficiency is high.

The invention discloses a clearing method, system and apparatus for the power spot market. The method comprises firstly establishing a DC power flow constraint model; calculating the power output planparameter of a power generating set according to the DC power flow constraint model to obtain the preliminary result of the power spot market clearing optimization; obtaining the power flow values ofrespective branches by performing AC safety check calculation on the power output plan parameter; and correcting the DC power flow constraint model according to respective power flow values. The solution accuracy is improved based on the DC power flow constraint model. Performing AC safety check calculation on the power output plan parameter obtained by DC power flow constraint calculation is quicker than directly using AC power flow constraint calculation. Therefore, the method provided by the present invention takes account of solution accuracy and calculation speed, and more satisfies thepower spot market clearing optimization required by the actual engineering application than the prior art. The invention also discloses a clearing system and apparatus for the power spot market and acomputer readable storage medium, which have the above beneficial effects.

The invention relates to a four-rotor UAV (unmanned aerial vehicle) attitude control parameter tuning method based on an improved fish swarm algorithm. Based on a standard artificial fish swarm algorithm, the invention provides a strategy for dynamically adjusting an artificial fish moving step length, an elitist preservation and reproductive behavior and an external fishing behavior are introduced, and defects of series reduction of a later convergence speed, low convergence accuracy and easy falling into local optimum of a standard artificial fish swarm algorithm in the prior art are overcome. The method can be used for solving problems of aircraft design, flight control parameter tuning and path planning and has good problem solving accuracy and efficiency.

The invention discloses a calibrating method for an electronic compass. The calibrating method is used for promoting measuring accuracy of the electronic compass based on a self-adaption differential evolution algorithm and a Fourier neural network theory and is especially suitable for an orienting system with low cost and higher precision. The calibrating method comprises the following steps: utilizing a Fourier neural network to perform error modeling on the electronic compass and utilizing an improved self-adaption differential evolution algorithm to optimize a weight value of the Fourier neural network, so as to acquire an accurate error model to compensate a measuring value of the electronic compass. The error model which is established according to the calibrating method is capable of realizing accurate mapping of a sample space and has a higher nonlinear approaching capability. According to the calibrating method, a minimum local part is avoided, the defects of over-slow convergence rate and oscillation of the neural network are overcome and the influence of an outside magnetic field on the electronic compass is efficiently compensated, thereby greatly promoting the measuring accuracy of the electronic compass.

The invention provides a trajectory control method for a redundant mechanical arm. The method takes a redundant mechanical arm kinematic solving method of a configuration plane as the basis, deduces a speed distribution method of the configuration plane, determines the redundant mechanical arm movement locus planning process of speed distribution based on the configuration plane, deduces the key steps of movement planning: working configuration determination, spatial obstacle avoidance and speed distribution in the configuration plane, can meet the requirements of complex spatial obstacle avoidance, solves the indeterminacy of tail end point locus of the mechanical arm between spatial interpolation points, and can achieve a good movement locus. The invention solves a difficulty of inverse solution of a redundant mechanical arm, is advantageous in high calculation speed and high solving precision, and meets the demands of actual tasks and environment for the locus movement operation of the redundant mechanical arm.

The invention discloses a method for solving flexible job shop scheduling based on a hybrid whale swarm algorithm, and the method comprises the steps: firstly defining the coding mode of flexible jobshop scheduling as two-stage random key coding, and then carrying out the mapping conversion through employing a conversion mechanism; Defining the shortest total processing time for solving the fitness function as an optimization target; Secondly, initializing parameters and whale population in the flexible job shop scheduling problem by adopting a whale group algorithm, wherein initialization isdivided into a sorting scheme of a random generation process and a genetic variation mode of an improved genetic algorithm to generate a better machine distribution scheme corresponding to the sorting scheme of the process, and then a better initial population is generated; Calculating the fitness value of each scheduling scheme, and finding and reserving the best scheduling solution; And finally, outputting the optimal scheduling solution and the corresponding fitness function value to obtain a solved optimal scheduling scheme, and solving the problems of low solution precision and low convergence rate in the existing flexible job shop scheduling problem.

The invention discloses a semi-physical simulation landing guide analog system based on a decimeter-wave instrument landing system. The semi-physical simulation landing guide analog system is characterized by comprising a ground equipment simulator for simulating a localizer, a glide-slope localizer and a ranging response signal of the decimeter-wave instrument landing system according to an instruction of the simulator and providing simulated angle information and distance information for airborne equipment, and an airborne equipment simulator for demodulating and decoding the simulated information sent from the ground equipment simulator and providing the simulated information to a flying control system. The semi-physical simulation landing guide analog system has the beneficial effects that the processes of navigation audio signal generation, angle beacon calculation and calibration, control and detection and the like are all digitalized; the ground equipment simulator adopts a digital pulse amplitude modulation mode for generating a simulated high angular resolution signal, and the airborne equipment simulator adopts a digital filtering mode and the like for effectively improving the calculating precision and the ranging precision of an angle localizer; the circuit multiplexing degree is high, the working process is stable and reliable, and the intelligentization, integration and miniaturization are realized.

The invention discloses an integrated electrical and natural-gas energy system probability energy flow calculation method based on a stacked denoising autoencoder. The method comprises the following steps that: firstly, by virtue of the deep stack structure and the coding and decoding process of an SDAE (Stacked Denoising Autoencoder), establishing an energy flow model based on the SDAE to effectively mine the high-order characteristics of a nonlinear energy flow equation; on the basis, combining with numerical value characteristics input and output by the energy flow to put forward a trainingmethod based on a ReLU activation function, deviation standardization normalization and a small-batch gradient descent method to improve training accuracy and speed; and then, combining with an MCS (Modulation and Coding Scheme) method to sample a sample to be solved, and using a trained SDAE energy flow model to directly map the energy flow values of all sampled samples so as to realize the high-accuracy online calculation of the probability energy flow on a premise that hardware cost is not increased.

The invention discloses an interior point algorithm based LPV (Linear Parameter Varying) model nonlinear predicating control method. The method comprises the steps of linearizing a complex mechanism model of a system at a set working point to obtain a plurality of linear sub-models; selecting weight functions; weighting each linear sub-model to obtain a global approximation model of the system, namely, PLV model; treating the LPV model as the predicating model and selecting the secondary performance index function to create a nonlinear predicating control topic; solving the optimal topic by the interior point algorithm during rolling optimizing so as to obtain the optimal control sequence for achieving the nonlinear predication control. Compared with the prior art, the method has the advantages that the LPV-based full-simultaneous direct solving is performed, so that the solving precision is high, and the algorithm needs a little time; the control effect is obvious; the transition process of the system is reduced; the resource consumption is reduced; the control quality of the system is particularly obviously improved under a large variable working condition range.

The present invention relates to an electrical impedance tomography (EIT) method based on deep learning, and is applied to the technical fields of medical imaging, industrial process image and geological prospecting, etc. The method comprises: obtaining an original boundary measurement voltage sequence and a conductivity distribution sequence, and performing normalization processing to obtain a training sample set; establishing an initial EIT deep learning network model, and training the EIT deep learning network model according to the training sample set and the setting training mode to allow the EIT deep learning network model obtained through training to represent the mapping relation between the original boundary measurement voltage sequence and the conductivity distribution sequence; and inputting the boundary measurement voltage sequence to the mapping relation to obtain the conductivity distribution sequence, and finally recovering the conductivity distribution sequence to a matrix mode to obtain an EIT image. The electrical impedance tomography method based on deep learning simplifies the modeling process and the solution difficulty of problems so as to solve the nonlinearity and ill-conditioned problems when the electrical impedance inverse problem is solved and improve the solution precision of the inverse problem and the image reconstruction quality.

The invention discloses a method for image processing based on an improved fireworks algorithm, and relates to the field of image processing. The method comprises the following steps: initializing the positions of N fireworks grains, and recording the fireworks grains as initial grains G(old); calculating the position Sj of explosion spark generated by explosion of each fireworks grain, the explosion radius Aj of each fireworks grain and the position of mutation spark; selecting gains G(new) participating in next iteration from all the grains; determining optimal grains with best fitness values in all the gains included in both the initial grains G(old) and the gains G(new), and optimizing the grains except the optimal grains in the optimal value direction according to a bacterial foraging operator; and taking N grains with highest fitness as initial grains G(old) for next iteration from the optimized grains until an optimal solution is obtained. The improved fireworks algorithm can better overcome the poor result of the traditional fireworks algorithm in classification and regression, and effectively improves the result of optimal value point search.