Thus, fi is the normalized mean squared error (MSE) of the indivi

Thus, fi is the normalized mean squared error (MSE) of the individual i on the training set. The fitness variance σ2 is the symbol of particles convergence degree. When σ2 is smaller than a specified value σmin 2, the algorithm is considered as falling into precocity. Therefore, to avoid this drawback supplier AUY922 of basic PSO, a mutation mechanism based on resetting the velocity is proposed to enable particles

to have a new momentum. Under this new strategy, when σ2 < σmin 2, each particle i will be selected by a predefined probability from the population, and then a random perturbation is added to each dimension vjli (selected by a predefined probability) of velocity vector Vi of the selected particle i. The pseudocode of resetting velocity can be given as in Pseudocode 1, where p_1, p_2, and p_3 are separately generated and uniformly distributed random numbers in range (0, 1). Pseudocode 1 3.4. Flowchart of Proposed Method With above specific treatment, structure and parameters of the T-S CIN evolution can be implemented by IPSO. According to above description about the learning algorithm for T-S CIN, the proposed approach is an iterative

algorithm and can be coded easily on the computer, and the flowchart can be summarized as shown in Figure 4. Figure 4 Flowchart of proposed method. 4. Simulation Examples In this section, an example on the adjustment of shearer traction speed is provided to validate the proposed method. The aim of this study is to improve the accuracy and efficiency of identification for traction speed. Furthermore, the example can be divided into three main stages. Firstly, according to the working principle of shearer, the level of traction speed and mainly

evaluation indexes can be determined and the sample can be established reasonably. Secondly, according to the obtained evaluation indexes, the T-S CIN model can be constructed. Thirdly, the constructed standard T-S CIN, the T-S CIN with PSO, IPSO, and traditional T-S FNN, the T-S FNN with PSO, IPSO optimization are, respectively, tested with the same training and test samples to compare the accuracy and efficiency in adjustment of shearer traction speed. 4.1. Sample Preparation In a fully mechanized coal mining face, the adjustment of shearer traction speed should consider Batimastat the coordination with other coal mining equipment (scraper conveyor and hydraulic support). After the analysis of shearer working principle, the evaluation indexes of traction speed mainly consist of cutting motor current (CMC), cutting motor temperature (CMT), traction motor current (TMC), traction motor temperature (TMT), scraper conveyor current (SCC), and scraper conveyor speed (SCS). For a fixed shearer of MG 300/730-WD, the adjusting range of traction speed is 0~9.0m/min.

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