[PDF] Top 20 Traffic Signal Prediction Using Elman Neural Network and Particle Swarm Optimization
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Traffic Signal Prediction Using Elman Neural Network and Particle Swarm Optimization
... of particle swarm algorithm utilized in finding the optimal weights for the neural network included inertia parameter , and the coefficients of contributions from the local best and global ... See full document
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ASSOCIATION RULE MINING BASED VIDEO CLASSIFIER WITH LATE ACCEPTANCE HILL CLIMBING APPROACH
... a neural network ensemble model to perform the judgement of combustion diagnosis based on the spectral distribution of the light intensity pulse signal of the ...single neural network, ... See full document
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Protein Secondary Structure Prediction using Deep Neural Network and Particle Swarm Optimization Algorithm
... a Neural Network input ...feedforward neural network with backward propagation for weight update was employed ...deep neural network of five feedforward ...Deep Neural ... See full document
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Classification Credit Dataset Using Particle Swarm Optimization and Probabilistic Neural Network Models Based on the Dynamic Decay Learning Algorithm
... One another of first studies that became well-known in credit risk measurement was Z-score that is obtained from multi variable scoring model (Altman, 1968). This model is multiple discriminant analysis (MDA) that by ... See full document
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Fuzzy Artificial Neural Networks and Particle Swarm Optimization Based Enhanced Traffic Signal Controlling System
... a traffic signal control method using fuzzy artificial neural network at isolated intersection and ...A traffic light controller based on fuzzy artificial neural ... See full document
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HAND WRITING RECOGNITION USING HYBRID PARTICLE SWARM OPTIMIZATION & BACK PROPAGATION ALGORITHM
... Artificial Neural Network (ANN) has been around since the late ...and signal recognition. Artificial Neural Network (ANN) is a collection of very simple and massively interconnected ... See full document
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Particle swarm optimization for neural network learning enhancement
... Artificial Neural Network (ANN) or commonly referred as Neural Network (NN) is an information processing paradigm that is inspired by the way biological nervous systems process the ...loped ... See full document
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Dynamic Shortest Path Algorithm in Stochastic Traffic Networks Using PSO Based on Fluid Neural Network
... dynamic traffic assignment and route guidance in intelligent transporta- tion ...a Particle Swarm Optimization (PSO) algorithm with priority-based encoding scheme based on fluid neural ... See full document
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Enhancement of quantum particle swarm optimization in elman recurrent network with bounded VMAX function
... BP network, such as trap into local minima and may get stuck at regions of a search ...problems, Particle Swarm Optimization (PSO) has been executed to improve ANN ...errors ... See full document
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TB Diagnosis System using Genetic Particle Swarm Optimization Based Neural Network Classifier
... The fundamental plan of this method is to decrease the size of the feature vector by means of Multi kernel fuzzy c- means clustering in addition to roughest theory algorithm. Large feature set is a huge hindrance for the ... See full document
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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, ... See full document
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Learning enhancement of radial basis function neural network with harmony search algorithm
... global optimization methods could be applied for training RBF networks in accordance with the various science and engineering ...the particle swarm optimization (PSO) algorithm, the artificial ... See full document
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Optimized Neural Network-Based Improved Multiverse Optimizer Algorithm For Automated Arabic Essay Scoring
... than using k-NN with ...measured using term frequency and inverse document frequency (tf-idf) and cosine correspondence ...system using 30 written ...frequent neural networks to handle the ... See full document
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Artificial Neural Network and Particle Swarm Optimization in Orange Identification
... Nasirahmadi and his associate Ashtiani S in their paper have grouped fruits and classified them using Image processing combined with pattern recognition. They classified 20 varieties almonds which are of sweet and ... See full document
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Parallel Implementation of Particle Swarm Optimization Variants Using Graphics Processing Unit Platform
... variable number of iteration, we set predefined optimum value for all benchmark test functions, and maximum speedup were 10.9, 62.91, and 27.63 for TPSO, APSO, and ALC-PSO algorithms, respectively. In fixed number of ... See full document
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FUZZY BASED DETECTION AND SWARM BASED AUTHENTICATED ROUTING IN MANET
... MLP neural networks include units in layers, each layer being composed of nodes and in a fully connected network each node connect subsequent layer ...each signal feeding a subsequent layer node has ... See full document
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COMPARATIVE STUDY OF INTELLIGENT TECHNIQUES FOR SOLVING OPF PROBLEM
... Jithendranath, J. ; Babu, B.Y.[23] presents a significant evolutionary based algorithm for solving conventional Optimal Reactive Power Dispatch (ORPD) problem in power system. This problem was designed as a Multi- ... See full document
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Particle Swarm Optimization Feedforward Neural Network for Hourly Rainfall-runoff Modeling in Bedup Basin, Malaysia
... The “pbest” value (each particle’s lowest learning error so far) and “gbest” value (lowest learning error found in entire learning process so far) are applied to the velocity update equation (Eq. 2) to produce a value ... See full document
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A Comparison Between GA and PSO Algorithms in Training ANN to Predict the Refractive Index of Binary Liquid Solutions
... a swarm and the individuals are called particles. Each particle in the swarm may be considered as a candidate ...Each particle may move with a compatible velocity through the search ...a ... See full document
11
Parameter optimization of evolving spiking neural networks using improved firefly algorithm for classification tasks
... al., 2009). Despite that, ESNN is affected by the selection of parameters, in which case the right selection of parameters will allow the network to develop towards a more effective structure. In Hamed et al. ... See full document
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