Titlebook: Artificial Neural Nets and Genetic Algorithms; Proceedings of the I Andrej Dobnikar,Nigel C. Steele,Rudolf F. Albrecht Conference proceedin

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書目名稱Artificial Neural Nets and Genetic Algorithms影響因子(影響力)




書目名稱Artificial Neural Nets and Genetic Algorithms影響因子(影響力)學(xué)科排名




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書目名稱Artificial Neural Nets and Genetic Algorithms被引頻次學(xué)科排名




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書目名稱Artificial Neural Nets and Genetic Algorithms年度引用學(xué)科排名




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書目名稱Artificial Neural Nets and Genetic Algorithms讀者反饋學(xué)科排名

Patrimony

Neural Dynamic Model for Optimization of Complex Systems this patent and its application to design automation and optimization of large one-of-a-kind engineering systems. We also show the successful application of this model to another nonlinear optimization problem, construction scheduling and cost optimization.

GULP

暗指

A Quantum Associative Memory Based on Grover’s Algorithmy faster than their classical counterparts. The unique characteristics of quantum theory may also be used to create a quantum associative memory with a capacity exponential in the number of neurons. This paper combines two quantum computational algorithms to produce a quantum associative memory. The

指派

Newton Filters: a New Class of Neuron-Like Discrete Filters and an Application to Image Processingse the area where it receives information from. The number of dentritic ramifications is not constant, it depends on the neuron and varies from one to the other. Moreover, each dentritic tree can be subdivided in a complex form leading to a characteristic tree structure [1]. Two of their immediately

altruism

Improving Generalisation Using Modular Neural Networkstectures for modelling. The convention in neural networks is to use as small an architecture as possible to force better generalisation by modelling the underlying distribution and ignoring the details [1]. This practice involves the loss of information from the training data which in real world dom

Fracture

踉蹌

A Curvature Primal Sketch Neural Network Recognition Systemimage onto the input nodes of a feed-forward net. This is problematic in that the topological properties of the original image space, such as the spatial relations between different pixels, are not immediately apparent to the net. We address this problem by using the real valued coordinates of selec

切掉

Using GMDH Neural Net and Neural Net With Switching Units to Find Rare Particlessing data simulated in SACLAY laboratory because the experiment ATLAS in CERN is still under construction. Because there are no direct criteria for separation of events, we use two kinds of neural nets for this task. The neural nets used have continuous output and separation — classification of even

使閉塞

A Neural Network Based Nonlinear Temporal-Spatial Noise Rejection Systemapability of these neural networks and related learning algorithms, the proposed system can offer better noise rejection performance than traditional methods in the case that the related unknown system is nonlinear or non-minimum phase and in the case that the length of the learning system does not