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Miner health assessment method and system
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A health assessment and health management system technology, applied in the field of human health management, can solve the problem of insufficient accuracy of data processing results, and achieve the effects of improving efficiency and reliability, reducing complexity, and speeding up learning.
Pending Publication Date: 2020-09-01
ANHUI UNIV OF SCI & TECH +1
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[0003] At present, the prediction and evaluation of miners' occupational diseases requires the use of data mining technology to analyze and evaluate the health data collected by the health management system. However, simple statistical methods are commonly used to process data, and the efficiency of data processing and the accuracy of the results obtained are not high enough.
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[0078] The step S3 adopts the ABC-RS algorithm to perform attribute reduction on the original miner health data, and the specific steps are as follows:
[0079] S31: Construct a decision table system S=(U,A,V,F), U is the universe of discourse, A=C∪D, A is the attribute set, C is the condition attribute, D is the decision attribute; the output is the decision table system S = A relative reduction of (U,A,V,F);
[0080] S32: Calculate the positive area POS of S with respect to the attribute set A A (D), that is:
[0081] POS A (D)=∪ X∈U / D IQ
[0082] In the formula, IQ is the lower approximation of the attribute subset I;
[0083] S33: Initialize the reconnaissance bee colony size W, follow the bee colony size W, the number of iterations is n, and the number of food sources for the bee colony is n;
[0084] S34: The reconnaissance bee searches for honey sources, and randomly generates W honey source positions x(i) (i=1, 2,...,W);
[0085] S35: The detective bee becomes the leading bee, le...
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Abstract
The invention discloses a miner health assessment method and system, and relates to the technical field of human health management. The method comprises the steps of 1, building a miner health management system; 2, collecting, by the system, physiological parameter data of miners with different health conditions; 3, performing attribute reduction on the original miner health data by adopting an ABC-RS algorithm; 4, randomly dividing the data subjected to attribute reduction into a training set and a prediction set in proportion; and 5, establishing an ELM health diagnosis prediction model by using the training set, and checking the effect of early occupational disease category prediction by using the prediction set. The ABC-RS algorithm and the ELM algorithm are combined to be used for processing, predicting and evaluating the physiological index data of miners; ABC-RS is adopted to delete useful attributes in the miner health data, an ELM health diagnosis prediction model is established by utilizing training sets randomly divided according to a proportion, the prediction set checks the classification effect, and finally evaluation of the miner health condition is realized.
Description
Technical field [0001] The invention relates to the technical field of human health management, in particular to a method and system for evaluating the health of miners. Background technique [0002] With the continuous increase of coal mining depth, the underground operating environment conditions are gradually deteriorating. With serious dust pollution and harsh environment in the workplace, the possibility of miners suffering from occupational hazards is greatly increased. The mechanism of the impact of dust, toxic gas, humidity and other harsh operating environments on the health of miners and the impact on the physical and mental health of miners are studied, and characteristic indicators are screened. It can realize the early judgment of occupational diseases, increase the early detection rate of occupational diseases, deepen people's awareness of health, and reduce the serious burden of occupational diseases and economics on miners. [0003] At this stage, the prediction an...
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