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101 results about "Life stage" patented technology

Rotating-machinery life-stage identification method based on deep self-encoding learning network of noise enhanced samples

The invention relates to a rotating-machinery life-stage identification method based on a deep self-encoding learning network of noise enhancement samples. For the purpose that extraction and expression of rotating-machinery life features as well as life stage identification are automatically learned under the condition of a small sample size, noise enhancement are conducted on training samples; after a plurality of sparse self codes are stacked, classification layers are added to construct the deep sparse self-encoding learning network which can not only automatically learn extraction of the life features, but also intelligently identify the life stages. Stepwise non-supervision adaptive learning and supervision fine tuning are conducted on the the samples obtained after noise enhancement through multi-layer sparse self encoding, so as to inhibit deep-network over fitting and improve network robustness. Therefore, automatic extraction and expression of the rotating-machinery life features are achieved, and finally intelligent identification of the rotating-machinery life stages in the classification layers are completed. The rotating-machinery life-stage identification method can be applied in identifying rolling bearing life stages, and identifying results are good under the condition of a small sample size.
Owner:CHONGQING JIAOTONG UNIVERSITY

Limit model training method and device, limit assessment method and device, equipment and medium

The invention discloses a limit model model training method, a limiting assessment method and device, equipment and a medium. The limit model training method comprises the following steps: screening original user data, and obtaining basic user data meeting a training standard, wherein the basic user data comprises a credit line, basic information data, basic asset data and basic consumption data;preprocessing the basic information data to obtain a corresponding life stage category; preprocessing the basic asset data to obtain a repayment capability level corresponding to the basic user data;preprocessing the basic consumption data to obtain a consumption capability level corresponding to the basic user data; marking the credit line, the life stage category, the repayment capability leveland the consumption capability level of the basic user data to obtain training data; training the training data by adopting a GBDT algorithm to obtain a pre-granted credit line model, and solving theproblem that the pre-granted credit line obtained through the pre-granted credit line model is inaccurate.
Owner:PING AN TECH (SHENZHEN) CO LTD

Method for predicating embryotoxicity of non-steroidal anti-inflammatory drug type novel pollutants on early-phase life stage of zebra fish

ActiveCN105044317AAddressing non-reflective typical NSAID sewage biotoxicityBiological testingLife stageFish embryo
The invention discloses a method for predicating the embryotoxicity of non-steroidal anti-inflammatory drug type novel pollutants on an early-phase life stage of zebra fish. The method comprises the following steps: exposing zebra fish embryos in the non-steroidal anti-inflammatory drug type novel pollutants which have equal logarithm space concentrations; recording the death rate and the aberration rate of the zebra fish embryos 7 days after exposing; and calculating by using SPSS software to obtain corresponding LC50 and teratogenetic EC50, which are used for evaluating the toxicity of the non-steroidal anti-inflammatory drug type novel pollutants. With the adoption of the method, the toxicity feature and the toxicity level of the non-steroidal anti-inflammatory drug type novel pollutants are subjected to an analytical test and quantitative description; and meanwhile, the method also can be used as an index for monitoring and evaluating the wastewater biological toxicity of non-steroidal anti-inflammatory drugs, and reference is provided for risk predication and evaluation of the potential biological toxicity of the pollutants in a water body.
Owner:GUANGDONG INST OF MICROBIOLOGY GUANGDONG DETECTION CENT OF MICROBIOLOGY
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