neural network optimization technique
Parkinson’s Disease Detection Using Biogeography-Based Optimization
... the neural network classifier produces the most accurate ...parallel neural network technique to increase the precision of PD ...(FKNN) technique to develop an efficient model ...
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Vol 7, No 9 (2017)
... used technique in cloud computing, that is used for implementing these three services along with VM migration techniques that is used for the maintenance of virtualized cloud computing data centers ...Swarm ...
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A Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems
... new technique for some types of FOCPs by means of a combination of the Mittag-Leffler function and artificial neural networks that so far has not been utilized for the FOCPs ...the neural ...
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A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction
... robust optimization capability of CRO, with its low number of tuning parameters, motivated us to adopt it as the learning ...neuro-fuzzy network (CNFN) model is validated by forecasting the daily closing ...
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Shape Optimization of Pedestals Using Artificial Neural Network
... this technique to find optimal shape of the downstream side of dams to eliminate tensile stress from the heel of the ...artificial neural networks in a gradientless method of shape ...shape ...
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Hybrid Neural Network Controller Design for a Batch Reactor to Produce Methyl Methacrylate
... control technique to control the ...the neural network forward model to predict the dynamics behavior and the neural network inverse model to control the process integrated with the ...
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Online Full Text
... an optimization technique using the back-propagation neural network to search for an optimal compression ratio to improve the quality of the signal and to improve the energy efficiency of the ...
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Plant Species Classification through New Feature Extraction Model Velocity Clamping Based Intersecting Cortical Model
... coupled neural network to segment the ...Coupled neural network entropy sequence with morphological features and has achieved more than 90% accuracy on leaf data ...Coupled network ...
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Medical Image Compression using Neural Network with HGAPSO Optimization
... Particle swarm optimization (PSO) is a popular optimization technique developed as an inspiration from the behaviour of swarm [12]. PSO search for a best optimal result by analyzing the activity and ...
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Frame Optimization using Neural Network
... of Neural-network (NN) technology stemmed from the desire to create an artificial system that could perform “intelligent” tasks similar to those performed by the human ...structural optimization ...
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A Novel Wireless Sensor Node Positioning Algorithm Based on Ant Colony Optimization Algorithm and Neural Network
... The ABC algorithm is an optimization technique that simulates the foraging behaviour of honey bees. In the ABC model, the colony consists of three groups of bees: employed bees, onlookers and scouts. It is ...
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An efficient and high-resolution topology optimization method based on convolutional neural networks
... Topology optimization is a pioneering design method that can provide various candidates with high mechanical ...topology optimization method is proposed based on the Super-Resolution Convolutional ...
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Neural Network Priority Use of BTS for Optimizing Telecommunications in Indonesia
... Abstract—Artificial Neural Network Backpropogation is used to measure the Utilization Priority of BTS (Base Transceiver Station) to Optimize Telecommunication in 3T Disadvantaged, Outermost, Inside Areas ...
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Deep Auto-Encoder Neural Network for Phishing Website Classification
... Jameel and George presented a feedforward neural network to classify the phishing email by mining features from the email’s slogan and HTML organization. Their proposed algorithm was verified on 18 features ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... of neural networks become ap- parent only for large-scale problems, which are computationally intensive and not feasible for hand ...MATLAB, neural network al- gorithms can be quickly implemented, ...
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Article Description
... The objective function aim to finding an acceptable or adequate design that merely satisfies the functional and other requirements of the problem. there will be more than one acceptable design, and the purpose of ...
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Neural Network and Adaptive Feature Extraction Technique for Pattern Recognition
... PCA Feature Extraction by Hebbian Algorithm The principal component analysis (PCA) is a Multivariate Statistical Process Control (MSPC) methods. Feature extraction methods determine an appropriate subspace of ...
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Investigating and Prioritizing Factors Affecting Health Literacy in University Students of Yazd Using Artificial Neural Network Technique
... Sensitivity analysis of independent variables on the RBF network showed that grade had the greatest impact on student health literacy. This finding is consistent with the findings of Rong et al. (19) who stated ...
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Optimizing Process Parameters of Rotary Furnace using Bio fuels: An Interactive ANN Approach
... Artificial neural network modeling is a tool which helps in knowing about the system and how it will behave in real ...(Feed-forward neural network model and backward neural ...
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DEEPWATER PRODUCTION FORECASTING USING COMPUTATIONAL INTELLIGENCE TECHNIQUES
... the network are adjusted in the course of an iterative process termed ...many network architectures but Multilayer Perception is the most popular among ...forward neural network input layer is ...
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