gradient-type neural network
MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... The proposed system presents a modeling of interactive game between regular mobile node and malicious mobile node as a dynamic Bayesian game [15] and later on finding the Perfect Bayesian equilibrium of the proposed ...
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... Assets have different shapes, colors and textures. A shape feature is the main characteristic, which distinguishes each type of asset in addition to the other features, i.e. the color and the texture. The value of ...
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... When a node decides to make a route and sends some data to one other node, it prepares a RREQ message. Source node will create a temporary public key and puts it in RREQ packet. RREQ should contain destination position ...
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Optimizing Back-Propagation Gradient for Classification by an Artificial Neural Network
... that may arise. In addition, during emergency cases, many optimization methods are proposed to reduce processing time and improve network performance, considering these constraints and characteristics related to ...
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... The most challenging task is to achieve the shortest path for a network by minimizing the cost (distance) inside a given area. The shortest path has been used extensively for other purposes, such as vehicle ...
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... pattern type detection we covered XOR, succession and parallel patterns and finally exposed our mining algorithm followed by the case study in the previous ...
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SCALED CONJUGATE GRADIENT NEURAL NETWORK MODELLING FOR PREDICTION OF CBR OF SOILS
... Feed-forward neural network is the most preferred ANN ...the network and the weight and bias values are adjusted and updated as the forward and back propagation ...
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Conjugate gradient neural network in prediction of clay behavior and parameters sensitivities
... artificial neural network model for sands based on grain size distribution and stress ...artificial neural network model within a finite element analysis to extract the geo-material ...
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... The first version of WFA was applied to solve the BPP. The algorithm mainly depended on neighbor solution searches. The result was favorable in quality of the solution, executed time and based on the result; the authors ...
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... this type of approach, the person interested in obtaining a diagnosis sends information through some communication channel (usually internet or telephone), and such an information is analyzed by a human ...
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Telecom Voice Traffic Prediction for GSM using Feed Forward Neural Network
... In this paper, our concentration is to find best correlated resource parameter for traffic prediction over GSM, search for faster training algorithm and to achieve good performance result for our model. Finding of mean ...
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Complex value recurrent neural networks for global optimization of beamforming in multi symbol MIMO communication systems
... dard neural network that involving some parameters to be tuned during the learning phase, the prin- cipal idea of using recurrent neural network for optimization is to appropriately construct ...
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Noise-Induced Hearing Loss (NIHL) Prediction in Humans Using a Modified Back Propagation Neural Network
... Conjugate Gradient Descent and conventional BPNN algorithm and it converges in considerably less iteration on XOR and SINEWAVE period ...Conjugate Gradient method, its success and failure rate is same like ...
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Face Recognition using Rectangular Feature
... a neural network. This neural network consists of three layers, 10 neurons in the first layer, 20 neurons in the hidden layer and one neuron in the output ...the neural network ...
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Artificial Neural Networks to Determine Source of Acoustic Emission and Damage Detection
... Multilayer neural networks which are sometimes referred to as perceptrons, are simple models of several connected neurons similar to what is seen in the natural neural networks of ...
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Investigation On Various Training Algorithms For Robust ANN-PID Controller Design
... Similarly, scaled conjugate algorithm has been used in hand gesture control of robotic arm [14], assessment of electromagnetic compatibility [15], etc. In all these cases, the algorithm for tuning artificial NN is taken ...
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Solar Irradiance Forecasting using Deep Neural Networks
... Figure 12 shows a sample of training data in four different weather conditions: few clouds, scattered, overcast, and clear-sky. The results of the predictive model are shown in Fig. 13. The actual data plotted with the ...
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Noise Induced Hearing Loss (NIHL) prediction in humans using a modified back propagation neural network
... Artificial Neural Networks (ANN) are modelled on the human brain and consists of processing units known as artificial neurons that can be trained to perform complex calculations like human ...
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... develops neural network (NN) method using conjugate gradient (CG) with combination of particle swarm optimization (PSO) and genetic algorithm ...of neural network, so that the addition ...
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... The proposed method have used skin color segmentation methods as well as edge detection to detect face in color images.. In addition, a template matching process is applied based on a li[r] ...
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