The current whaleoptimizationalgorithm(WOA)has several drawbacks,such as slow convergence,low solution accuracy and easy to fall into the local optimal *** overcome these drawbacks,an improved whaleoptimization Alg...
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The current whaleoptimizationalgorithm(WOA)has several drawbacks,such as slow convergence,low solution accuracy and easy to fall into the local optimal *** overcome these drawbacks,an improved whaleoptimizationalgorithm(IWOA)is proposed in this *** can enhance the global search capability by two ***,the crossover and mutation operations in Differential Evolutionary algorithm(DE)are combined with the whaleoptimization ***,the cloud adaptive inertia weight is introduced in the position update phase of WOA to divide the population into two subgroups,so as to balance the global search ability and local development *** and Matlab are used to establish the structure *** demonstrate the application of the IWOA,truss structural optimizations on 52-bar plane truss and 25-bar space truss were performed,and the results were are compared with that obtained by other optimization *** is verified that,compared with WOA,the IWOA has higher efficiency,fast convergence speed,better solution accuracy and *** IWOA can be used in the optimization design of large truss structures.
Precipitation is the most basic part of the water cycle process. Aiming at the problem of low prediction accuracy caused by the nonlinear and unstable characteristics of the precipitation series, a new precipitation p...
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Precipitation is the most basic part of the water cycle process. Aiming at the problem of low prediction accuracy caused by the nonlinear and unstable characteristics of the precipitation series, a new precipitation prediction method based on the CEEMDAN-IWOA-BP coupling model is proposed. This method first uses the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to decompose the original precipitation sequence, and obtains a series of intrinsic mode function (IMF) and residual terms (Res) as inherent potential influencing factors, innovatively introduce TENT chaotic mapping and roulette algorithm to improve the whaleoptimizationalgorithm (WOA), use IMFs and Res as the input of the improve whale optimization algorithm (IWOA) to optimize Back Propagation (BP) neural network prediction model, and finally superimpose the predicted values as ultima *** present method was applied to predict the annual precipitation from 1958 to 2017 in Sichuan Province. Compared with the prediction results of other models, the CEEMDAN-IWOA-BP coupled model has significantly improved prediction accuracy than the single model, and the prediction error index is smaller than the BP neural network optimized by the Genetic algorithm (GA) and Particle Swarm optimization (PSO) algorithms, moreover, the optimization accuracy and solving ability are significantly enhanced compared with the unimproved WOA. It can extract the information of complex precipitation series more effectively, and then provide a new method for nonlinear and unstable precipitation time series prediction.
In this study,an optimized long short-term memory(LSTM)network is proposed to predict the reliability and remaining useful life(RUL)of rolling bearings based on an improved whale-optimized algorithm(IWOA).The multi-do...
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In this study,an optimized long short-term memory(LSTM)network is proposed to predict the reliability and remaining useful life(RUL)of rolling bearings based on an improved whale-optimized algorithm(IWOA).The multi-domain features are extracted to construct the feature dataset because the single-domain features are difficult to characterize the performance degeneration of the rolling *** provide covariates for reliability assessment,a kernel principal component analysis is used to reduce the dimensionality of the features.A Weibull distribution proportional hazard model(WPHM)is used for the reliability assessment of rolling bearing,and a beluga whaleoptimization(BWO)algorithm is combined with maximum likelihood estimation(MLE)to improve the estimation accuracy of the model parameters of the WPHM,which provides the data basis for predicting *** the possible gradient explosion by training the rolling bearing lifetime data and the difficulties in selecting the key network parameters,an optimized LSTM network called the improved whaleoptimizationalgorithm-based long short-term memory(IWOA-LSTM)network is *** IWOA better jumps out of the local optimization,the fitting and prediction accuracies of the network are correspondingly *** experimental results show that compared with the whaleoptimizationalgorithm-based long short-term memory(WOA-LSTM)network,the reliability prediction and RUL prediction accuracies of the rolling bearing are improved by the proposed IWOA-LSTM network.
A star-delta connection winding structure can restrain the low order harmonic of armature magnetic field and improve the operating efficiency of machine. However, the risk of inter turn short circuit in its structure ...
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ISBN:
(纸本)9798350373486;9798350373479
A star-delta connection winding structure can restrain the low order harmonic of armature magnetic field and improve the operating efficiency of machine. However, the risk of inter turn short circuit in its structure is higher. In this paper, the short-circuit current of inter-turn short circuit occurring at different winding positions is derived. An adaptive weight strategy is used to improve whale optimization algorithm (WOA). The improved WOA is adopted for optimizing the parameters of variational mode decomposition (VMD). VMD based on improved WOA for processing current signal is proposed. Finally, by calculating the fuzzy entropy of current and torque, a fault diagnosis method for inter-turn short circuit fault in star-delta connection winding structure is proposed. The accuracy of this fault diagnosis method can reach over 90%. And it can effectively distinguish that the inter-turn short circuit fault occurs in Y connection part or. connection part.
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