In order to select appropriate logistics suppliers, and by using of advantages of bp neural networks with selforganizing, self- learning, anti- interference, etc. a logistics supplier selection model was constructed, ...
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ISBN:
(纸本)9781424455690
In order to select appropriate logistics suppliers, and by using of advantages of bp neural networks with selforganizing, self- learning, anti- interference, etc. a logistics supplier selection model was constructed, and an integrated logistics suppliers' capacity (performance) evaluation bp neural network was established, also, bp algorithm was designed. Then an example with twenty-three listed logistics suppliers' data in 2007 was studied. The example shows that the selection model is able to identify the evaluation level and size of alternative logistics suppliers, and provides an effective approach for selection of logistics suppliers.
Low-density parity-check (LDPC) codes deliver very good performance when decoded with the bp algorithm. Unfortunately, this algorithm has the disadvantage to be complex for implementation. In this paper, we investigat...
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ISBN:
(纸本)9781424416875
Low-density parity-check (LDPC) codes deliver very good performance when decoded with the bp algorithm. Unfortunately, this algorithm has the disadvantage to be complex for implementation. In this paper, we investigate the bp algorithm and its simplifications (bp-Based, normalized bp-Based, offset bp-Based). Previous works on normalized and offset bp-Based proposed theoretical values for the offset and normalization factors, we perform simulations which allow to validate these theoretical results.
The back propagation (bp) model of artificial neural networks (ANN) has many good qualities comparing with ordinary methods in land suitability *** analyzing ordinary methods’ limitations,some sticking points of bp m...
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The back propagation (bp) model of artificial neural networks (ANN) has many good qualities comparing with ordinary methods in land suitability *** analyzing ordinary methods’ limitations,some sticking points of bp model used in land evaluation,such as network structure,learning algorithm,etc.,are discussed in detail,The land evaluation of Qionghai city is used as a case *** comprehensive assessment method was also employed in this evaluation for validating and comparing.
\In this paper, a new kind of intelligent PID control method based on bp neural network is presented and a complex neural network PID controller is designed. The NN controller has strong self-adaptability and self-lea...
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ISBN:
(纸本)9780769538167
\In this paper, a new kind of intelligent PID control method based on bp neural network is presented and a complex neural network PID controller is designed. The NN controller has strong self-adaptability and self-learning abilities. Experimental results on different complex objects prove that, the control method has better performances than traditional PID controller. The system using neural network has high control accuracy, strong adaptability and good control results.
It's very important to control the electrode current of arc furnace. This paper firstly discuss intelligent control method of arc furnace based on neural network, then the three-phase current prediction model of a...
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ISBN:
(纸本)9780769536828
It's very important to control the electrode current of arc furnace. This paper firstly discuss intelligent control method of arc furnace based on neural network, then the three-phase current prediction model of arc furnace has been built and it is analyzed and simulated by matlab software. The result shows that the electrode is effective controlled and the effect by using improved bp method is satisfactory.
This paper proposes a new approach for training FNN by, hybrid DE and bp. It combines the advantages of the global search performed by DE over the FNN parameter space and the local search of bp. Using a function appro...
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ISBN:
(纸本)0387283188
This paper proposes a new approach for training FNN by, hybrid DE and bp. It combines the advantages of the global search performed by DE over the FNN parameter space and the local search of bp. Using a function approximation as an illustration, we compare the HDEbp and bp for effectiveness and efficiency for training FNN. It shows that the use of new method can provide better results than bp.
Neural network has good fault-tolerant ability, classification ability, parallel processing ability and so on, so the research of software reliability model based on neural network is paid more and more attention. bp ...
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ISBN:
(纸本)9781538669532
Neural network has good fault-tolerant ability, classification ability, parallel processing ability and so on, so the research of software reliability model based on neural network is paid more and more attention. bp neural network has strong nonlinear mapping ability and flexible network structure, so bp neural network is currently used in various fields. In this paper, a software reliability model optimized by hidden layer bp neural network is proposed and the training process of bp algorithm on this model is described.
If sedimentation of constructions exceeds the prescribed limits, it would give rise to huge losses for community and people, so it is significant to establish the effective and practical deformation forcasting model f...
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ISBN:
(纸本)9780769536828
If sedimentation of constructions exceeds the prescribed limits, it would give rise to huge losses for community and people, so it is significant to establish the effective and practical deformation forcasting model for the safe operation and economic development. With the unique non-linear, non-convexity, non-locality, non-steadiness, adaptability and powerful ability of calulation and information process, bp (Back Propagation) neural network can adapt to the complicated and changeable dynamic characteristics of buildings,that has broad application foreground in deformation prediction. In this paper, on the basis of deformation observation data, a basic algorithm about establishing bp neural network model in sedimentation prediction is presented at the same time, analysis of examples are gived so that the application of neural network for deforamtion forcasting is studied comprehensively and systemically, the results show that neural network is very effective for Sedimentation prediction and can serve society and people in the future.
The fuzzy controller with neural network is proposed in this paper, this system consists of a fuzzy neural network controller and a model identification network, the fuzzy neural network controller is optimized by the...
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ISBN:
(纸本)9781424425020
The fuzzy controller with neural network is proposed in this paper, this system consists of a fuzzy neural network controller and a model identification network, the fuzzy neural network controller is optimized by the offline genetic algorithm of global searching ability, and the online bp algorithm ability of local searching. The detailed control algorithm is given, the algorithm of system identification based on modified Elman network is ratiocinated. The simulation result shows the feasibility and validity of the proposed method.
On-Line Learning Behavior depend on learning subject self-control learning, collaborative learning, and obtaining of support and help. Based on learning subject, the On-Line learning behavior need the real-time monito...
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ISBN:
(纸本)9781467383028
On-Line Learning Behavior depend on learning subject self-control learning, collaborative learning, and obtaining of support and help. Based on learning subject, the On-Line learning behavior need the real-time monitoring and the effective instruction to through the evaluation in the learning process. The bp algorithm model of evaluating ELearning behavior selects the learning behavior which affects the study effect in network learning process, has established the network learning behavior evaluating indicator system, and takes the data-in by the second-level target, carries on the network training using MATLAB, In the network training process, the global error assumes the declining trend basically, the restraining effect is good. Through the test indicated that this model may use in evaluating the network learning behavior, and obtains the expectation effect.
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