Titlebook: Artificial Intelligence and Soft Computing; 12th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

Objective

書目名稱Artificial Intelligence and Soft Computing影響因子(影響力)




書目名稱Artificial Intelligence and Soft Computing影響因子(影響力)學(xué)科排名




書目名稱Artificial Intelligence and Soft Computing網(wǎng)絡(luò)公開度




書目名稱Artificial Intelligence and Soft Computing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Artificial Intelligence and Soft Computing被引頻次




書目名稱Artificial Intelligence and Soft Computing被引頻次學(xué)科排名




書目名稱Artificial Intelligence and Soft Computing年度引用




書目名稱Artificial Intelligence and Soft Computing年度引用學(xué)科排名




書目名稱Artificial Intelligence and Soft Computing讀者反饋




書目名稱Artificial Intelligence and Soft Computing讀者反饋學(xué)科排名

Anonymous

Brain-Waves

licence

幻影

Agent-Based Population Learning Algorithm for RBF Network Tuning the data under analysis. The performance of the RBF network depends on numerous factors. One of them is a value of the RBF shape parameter. This parameter has a direct impact on performance of the transfer function of each hidden unit. Values of the transfer function parameters, including the value

透明

DEAWL

Reinforcement Learning in Discrete Neural Control of the Underactuated Systemon-line adaptation of a neural network. The controlled system is of the ball and beam type, which is the nonlinear dynamical object with the number of control signals smaller than the number of degrees of freedom. The main part of the neural control system is the actor-critic structure, that comes u

Ambiguous

Associative Text Representation and Correctionnces. Text descriptions allow us define new terms, gather knowledge and learn more quickly thanks to the associative mechanisms that work in our brains. Automatic and intelligent text processing and compression are very important nowadays. This paper introduces a novelty associative way of storing,

館長

Some Aspects of Neural Network State Variable Estimator Improvement in Induction Motor Drivereference frame with the help of neural networks. Some modification of the training procedure is considered that leads to the estimator accuracy improvement. Provided tests confirmed this feature but further steps are necessary to increase state variables estimation in the low supplying frequency ra

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