45 results about "Random search algorithm" patented technology

According to some embodiments, a thermostat obtains real-time energy prices from a electricity grid. It may also obtain additional data from external data sources, such as predicted energy prices or weather predictions. The thermostat attempts to find a control strategy for when to switch available aggregates that may include furnaces and air conditioners on and off. In order to solve this integer programming problem, the thermostat uses a random search algorithm. According to some embodiments, various data sources, such as day-ahead prices and real-time prices, are combined into forecasts of electricity prices for the present and future time periods. In some embodiments, a thermostat selects predictively between heating or cooling by letting outside air in or by using heating and cooling aggregates. Additional embodiments are discussed and shown.

The invention relates to a query optimization method based on a simulated annealing algorithm. The method comprises the steps that a data query optimization process is divided into a model building part, a strategy space resolving part and an optimization part, then the simulated annealing algorithm is led in, all strategy space subsets are searched in a parallel mode, a final solution is obtained from each subset, and the optimal solution is obtained after the final solutions are compared. Compared with other intelligent optimization algorithms, the simulated annealing algorithm can effectively avoid a local extremum and shorten the optimization time. In addition, due to the utilization of parallel searching, the searching range of the simulated annealing algorithm is enlarged, and the influence on searching precision by local search characteristics of the simulated annealing algorithm can be reduced. Compared with the probability for searching an optimal strategy by a traditional local random searching algorithm, the probability for obtaining the optimal strategy by the query optimization method based on the simulated annealing algorithm is improved obviously. The query speed of a database is improved, the relative time of query optimization is shortened, and the probability for obtaining the optimal strategy is improved.

The invention provides an oil deposit well pattern and injection-production scheme optimum design method based on a balanced water drive idea. The method comprises the steps of 1, collecting and arranging block geological and development related data; 2, setting optimizing related parameters, and completing the well pattern and injection-production optimization preparation work; 3, adopting an oildeposit engineering method, predicting the displacement condition on each direction under current well location and injection-production parameters and performing quantitative evaluation; 4, adoptinga global random search algorithm, optimizing and generating novel well location / injection-production parameters, and predicting and evaluating the displacement condition in each injection-productiondirection under novel well location injection-production parameters; 5, arranging the optimization result, forming a well pattern injection-production design scheme, and performing on-site implementation. According to the method, the water drive development index calculation method built on the basis of the oil deposit engineering idea is combined with the optimization theory, the global random search algorithm is adopted for automatic solving, the calculation efficiency is ensured while the well pattern and injection-production scheme matched with the actual oil deposit is obtained, and the oil deposit recovery efficiency is improved.

Described here are systems and methods for knowledge-based brachytherapy planning. These systems and methods are capable of automatically generating treatment plans for prostate brachytherapy in clinically relevant times. Primitive features computed from anatomical contours of the target organ are used to retrieve a template plan from a database. The template plan is then adjusted in a stochastic search algorithm.

The invention discloses a WSAN actuator task distribution method based on BA-BPNN data fusion, and the method employs a BA optimization BP neural network to build a data fusion model. The method specifically comprises the steps: employing a bat algorithm to optimize the weight value and threshold value of the BP neural network, building a data fusion model, carrying out the data fusion of the sensor node information, and obtaining the task distribution information of an actuator node. The bat algorithm is a meta heuristic type group intelligent optimization algorithm, employs an echo positioning method of a miniature bat under the condition of different transmitting speeds and responses, can achieve a precise capturing and obstacle avoidance random search algorithm. The BP neural network is a multilayer feedforward neural network which can search a global optimal value in a training process, and can increase the convergence rate of the network. The method searches the optimal parameter of the BP neural network through the positioning updating of bats, is more precise in data fusion, and is more reasonable in task distribution of an actuator.