[PDF] Top 20 Artificial Neural Networks Approach for Solving Stokes Problem

Artificial Neural Networks Approach for Solving Stokes Problem

... a neural network whose weights and biases are to be adjusted in order to deal with the mini- mization ...the problem has been reduced from the original constrained optimization problem to an ... See full document

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Title: CLASSIFICATION ON BREAST CANCER USING GENETIC ALGORITHM TRAINED NEURAL NETWORK

... training neural networks are based on local search, population methods, and others such as cooperative coevolutionary models ...for solving classification ...same problem with a differential ... See full document

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On the convergence speed of artificial neural networks in‎ ‎the solving of linear ‎systems

... basic problem in this rule is that, by choosing an unsuitable value for η the convergence speed is changed and also the method dont converge to the desired ... See full document

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Intrusion Detection System Using Hybrid Approach by MLP and K-Means Clustering

... Here author proposed a technique in which first step is to divide the large amount of data into small subset of data. For this k-means clustering is used. Once the cluster is formed for classification or labeling ... See full document

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Solving the Carbon Dioxide Emission Estimation Problem: An Artificial Neural Network Model

... in solving numerous problems in different world fields such as business [14], forecasting [15], fea- ture extraction [16], classifications [17,18] ...Back-propagation Neural Networks, which is the ... See full document

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Steganography Detection using Functional Link Artificial Neural Networks

... new approach known as Steganography detection using Functional Link Artificial Neural Networks that deals with neural network models that are able to detect Steganography content coded ... See full document

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An approach of curing Depression by Artificial Neural Networks (ANN)

... the neural network if the links between any of the nodes get disrupted then there can also be a faulty message transmission; leading to erroneous results but damaged artificial neurons can be readily ... See full document

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Artificial Neural Networks Approach in Microwave Filter Tuning

... Numerous different methods concerning filter tuning algorithms were presented in previous publications. In [1], filter tuning in time domain is shown. The described method requires a correctly tuned filter serving as a ... See full document

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Solving the linear interval tolerance problem for weight initialization of neural networks

... a neural network is considered a parameter estimation problem dealing with uncertainty about the initial ...problems. Solving a tolerance problem is defining lower and upper bounds of the ... See full document

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An Evolutionary Approach: Analysis of Artificial Neural Networks

... classification problem of high commercial importance is Optical Character Recognition ...the problem of processing a scanned image of text and transcribing it in to a machine readable form (in ASCII form or ... See full document

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Combat aircraft effectiveness prediction by artificial neural networks

... the approach by ranking order approximation inevitably contains unexplained factor and insensitive to the search of potential ...study. Artificial Neural Networks (ANN) is originated by ... See full document

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A. Artificial Neural Networks

... enhance artificial neural networks methods to support the prediction in stock market ...a neural network model for technical analysis of stock market, and its application to a buying and ... See full document

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Analysis of cardiovascular (cvd)/coronary heart diseases(chd) using artificial neural network (ann)

... the neural network refers to a network of biological neurons. Artificial neural network (ANN) is the mimicking of the human neuron on a ...neurons.[1][2]. Artificial neural ... See full document

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Data driven Time Series Based Prediction in Smart Home Appliance Energy Consumption

... using artificial intelligence (AI) methods such as support vector machine (SVM) and artificial neural networks (ANN) is a potential approach for such ...based approach to an ... See full document

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A Study on Effective Algorithm for Medical Decision Making System

... the neural diagnostic system. Then, paradigm of artificial neural networks is shortly introduced and the main problems of medical data base and the basic approaches for training and testing a ... See full document

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Approximating ground states by neural network quantum states

... many-body problem in quantum physics originates from the difficulty of describing the non-trivial correlations encoded in the exponential complexity of the many-body wave ...titled solving the quantum ... See full document

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Solving the Linearly Inseparable XOR Problem with Spiking Neural Networks

... generation artificial neural networks, the threshold is a simple binary step function, an artificial neuron in its simplest ...of solving linearly inseparable problems, such as the XOR ... See full document

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To contemplate quantitative and qualitative water features by neural networks method

... Hydrological models solving rainfall-runoff process can be split to deterministic and stochastic (Foumpaur 1999). Deterministic models divide to conceptual models, which contain a part of empirical relations and ... See full document

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Neural, Genetic, And Neurogenetic Approaches For Solving The 0-1 Multidimensional Knapsack Problem

... ST. Neural approach with KMW-M, in 100 iterations, reduced the deviation to ...iterations. Neural approach with ST-M reduced the deviation to ...that Neural approach provided ... See full document

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A FORMAL DEFINITION OF METRICS FOR OBJECT ORIENTED DESIGN: MOOD METRICS

... An artificial neural network (ANN), also called a neural network, is a widely used mathematical model composed of an interconnected group of simple artificial neurons that also called nodes, ... See full document

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