novel neural network algorithm
A Novel Wireless Sensor Node Positioning Algorithm Based on Ant Colony Optimization Algorithm and Neural Network
... In node positioning, the intensity of the received signal is usually determined by range-based algorithms. It is inevitable that the signal intensity would be disturbed by noises like airflow and multipath. In this case, ...
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A Novel Method of Rainfall Prediction using MLP FFN and Hybrid Neural Network Algorithm
... This paper reports a definite study on precipitation expectations utilizing diverse neural system structures more than a quarter century. From the study it has been discovered that the majority of the analysts ...
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A NOVEL IMAGE ENHANCEMENT METHOD USING GENETIC ALGORITHM AND NEURAL NETWORK
... combined, Neural Network has to be trained and on the basis of the training provided to the neural network the result would be evaluated that how much erosion has to be done in the image to ...
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Implementation of Evolutionary Computing Techniques for Cancer Diagnosis Using Digital Signal Processor
... a novel approach to implement Evolutionary Computing (EI) techniques like Fuzzy Logic, Genetic Algorithm, Neural Network, and Adoptive Neuro-Fuzzy Inference System (ANFIS) for diagnosis of ...
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PP and PP Multi Particles Production Investigation Based on CCNN Black Box Approach
... the novel application of an artificial neural network (ANN) black-box modeling approach based on the cascade correlation (CC) algorithm formulated to calculate and predict multiplicity ...
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Combination of uniform design with artificial neural network coupling genetic algorithm: an effective way to obtain high yield of biomass and algicidal compound of a novel HABs control actinomycete
... In recent years, more and more newly developed optimization strategies have been used in the fermenta- tion industry. And the problems in optimizing the yield of algicidal compound seems solvable though the ad- vanced ...
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Semantics Interaction Control for Constructing Intelligent Ecology of Internet of Things and Critical Component Research
... of novel intelligent deep hybrid neural network algorithm based on a deep bidirec- tional recurrent neural network integrated with a deep backward propagation neural ...
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DETECTING MOTION BY COMBINING THE STRUCTURE TEXTURE IMAGE DECOMPOSITION AND SPACE TIME INTEREST POINTS
... (DE) algorithm for training higher order neural networks (HONNs), especially the Pi-Sigma Network (PSN) has been ...proposed algorithm is a variant of DE/rand/2/bin and possesses two ...
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Deep Learning Approach Model for Vehicle Classification using Artificial Neural Network
... following novel features: (1) reducing the search space significantly compared to the sliding-window approach by using the Mean-shift algorithm; and (2) the use of deep learning approaches to extract highly ...
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SUPERVISED MACHINE LEARNING ALGORITHMS: DEVELOPING AN EFFECTIVE USABILITY OF COMPUTERIZED TOMOGRAPHY DATA IN THE EARLY DETECTION OF LUNG CANCER IN SMALL CELL
... a novel neural-network based algorithm, which we refer to as entropy degradation method (EDM), to detect small cell lung cancer (SCLC) from computed tomography (CT) ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... each network input, the algorithm is only given a ...to network inputs ...a network if you don’t know what it is supposed to do? Most of these algorithms perform some kind of clustering ...
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A New Method for Intrusion Detection Using Genetic Algorithm and Neural network
... evolutionary algorithm to determine the characteristics, the ability of the algorithm to search all the parts of the search space in the network and its ability to exploit the best ...This ...
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Classification Using Two Layer Neural Network Back Propagation Algorithm
... Dataset consists of 998 records each of which is characterized by nine attributes given in Table 2. [11] pro- posed the classification of malignant and benign tumor feature extraction algorithms based on principal compo- ...
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End-to-End Training of Deep Visuomotor Policies
... the neural network was trained to insert the peg without precise knowledge of the position of the hole, resulting in a partially observed ...the neural network, and the policies therefore had ...
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FLEXIBLE SHARING IN DHT BASED P2P NETWORKS USING METADATA OF RESOURCE
... NN algorithm, we first initialize some parameters, and then a set of data is employed to train to neural network to get the neuron ...trained neural network to estimate the direction- ...
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Testing of Rounded Corner for Micro-Drill on Hybrid of BP Neural Network and Adaptive Particle Swarm Optimization
... If the evolution speed of particle is fast, the algorithm can search optimization solving at large scope, if its evolution speed is slow, we can search at small space. On the other hand, if the square deviation of ...
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USE OF GENETIC SVM FOR ECG ARRHYTHMIA CLASSIFICATION
... BP learning Algorithm: There are two kinds of learning algorithm: Supervised and unsupervised .In the former ,the system weights are randomly assigned at he beginning and then progressively modified in the ...
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OPTIMIZATION OF HIGH VOLTAGE POWER SUPPLY FOR INDUSTRIAL MICROWAVE GENERATORS FOR ONE MAGNETRON
... genetic algorithm optimization, consider the nonlinear neural network capacity, combining these and forming the method of evolutionary neural ...tectonic neural network learning ...
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New Approaches for Image Compression Using Neural Network
... Levenberg-Marquardt algorithm results are summarized in Table ...Levenberg-Marquardt algorithm, due to large size of image, the matrix size is also large and it is not possible to perform more ...
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Mill Load Control System Based on the Improved Ant Colony Neural Network
... In the basic ant colony algorithm, subinterval with the largest information amount in the next node was selected according to the probability of p . Furthermore, the path with the maximum information amount was ...
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