Method for predicting concentration of chlorophyll a in water body based on harmony searching of cloud model
A concentration prediction, chlorophyll technology, applied in character and pattern recognition, special data processing applications, instruments, etc., can solve problems such as slow convergence speed and falling into local optimum.
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[0058] Step 1, determine the area that needs to predict the concentration of chlorophyll a in the water body, collect water samples in this area for ND=50 consecutive days, detect the concentration of chlorophyll a in the collected water samples every day, and the water quality indicators associated with chlorophyll a: ammonia nitrogen, total nitrogen , total phosphorus, orthophosphate, permanganate index, nitrate nitrogen, water temperature, dissolved oxygen, pH value, five-day biochemical oxygen demand, and the detected water quality indicators as a sample data set;
[0059] Step 2, normalize the collected water quality index sample data set, set the first 70% as the training data set of the support vector machine, and set the last 30% as the test data set;
[0060] Step 3, the user initializes the prediction span days AN=2, the harmony library size Popsize=50, the memory library learning rate HMCR=0.95, the pitch adjustment rate PAR=0.6, and the maximum evaluation times MAX_...
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