functional link network model
Training Neural networks for Experimental models: Classifying Biomedical Datasets for Sickle Cell Disease
... neural network approaches: Back-propagation trained feed-forward neural net classifier, Functional Link neural Network, the Radial basis neural Network Classifiers, and the Voted ...
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Steganography Detection using Functional Link Artificial Neural Networks
... using Functional Link Artificial Neural Networks that deals with neural network models that are able to detect Steganography content coded by a program ...Neural network methods are flexible ...
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Estimating Effort in Comprehensive Software Development Using NN, ABE, GAFLANN
... neural network architectures. The proposed ABE model increases the accuracy and each technique have different results which will be shown using ...(ABE), Functional Link Artificial Neural ...
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Parsimonious Random Vector Functional Link Network for Data Streams
... vector functional link networks (RVFLNs) is not scalable for data stream analytics because they work under a batch learning scenario and lack a self-organizing ...vector functional link ...
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Parsimonious random vector functional link network for data streams
... vector functional link net- works (RVFLNs) is not scalable for data stream analytics because they work under a batched learning scenario and lack a self-organizing ...vector functional link ...
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SME DEVELOPMENT BASED ON INFORMATION AND COMMUNICATION TECHNOLOGY TO GLOBAL MARKET IN DISTRICT KENDAL
... Neural Network (ANN), Fuzzy Set Theory and Rough Set ...Neural Network [2, 3], Local Linear Wavelet Neural Network (LLWNN) [4] and Functional Link Artificial Neural Network ...
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A hybrid Deep Boltzmann Functional Link Network for classification problems
... Boltzmann Functional Link Network (DBFLN) for classification ...generative model that is used to generate stochastic features and input weights for the discriminative ...discriminative ...
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Travel time measure specification by functional approximation: application of radial basis function neural networks
... a functional approximation, where measurements on traffic variables, ...of link travel times from link flow and occupancy data is discussed in several works, including, the explicit consideration of ...
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Application of functional link neural network to HVAC thermal dynamic system identification
... the network to represent the inverse of the plant, but there are potential drawbacks to this ...inverse model can be obtained if the nonlinear system mapping is not one to ...neural network ...
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A functional link neural network with modified cuckoo search for prediction tasks
... (MLP) network model is already well-established based on problem solving in pattern recognition (Ghazali & Al-Jumeily, 2009), classification (Fallahnezhad et ...of network that lie in HONN where ...
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Adaptive Channel Equalizer using Combination of FIR and Functional Link Artificial Neural Network for Complex Signals
... We have developed a proper artificial neural network (ANN) model for adaptive nonlinear channel equalization for multilevel signals. The prime advantages of using ANN models are their ability to learn which ...
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A hybrid Evolutionary Functional Link Artificial Neural Network for Data mining and Classification
... (HFLANN) model based on three metaheuristics population based optimization tools such: genetic algorithms (GAs), particle swarm optimization (PSO) and differential ...This model will be compared to the ...
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Training a functional link neural network using an artificial bee colony for solving a classification problems
... In this model, the colony of artificial bees consists of three groups: which are employed bees, onlookers and scouts [32]. For each food source there is only one artifi- cial employed bee. The number of employed ...
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Development of Improved Artificial Neural Network Model for Stock Market Prediction
... Neural Network (ANN) is a technique that is heavily researched and widely used in applications for engineering and scientific fields for various purposes ranging from control systems to artificial ...best ...
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Functional link neural network with modified bee firefly learning algorithm for classification task
... 2 In the field of Machine Learning (ML), ANNs is known as a family of statistical learning algorithm inspired by the way of human brain process information (Michalski et al., 2013). They are data driven self-adaptive ...
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A Systematic Approach for Testing and Debugging the Networks with ATPG
... device-independent model. The model is used to generate a minimum set of test packets to (minimally) exercise every link in the network or (maximally) exercise every rule in the ...backbone ...
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Adaptive Digital Image Filter using Functional Link Artificial Neural Network
... The functional link artificial neural network (FLANN) by Pao [12] can be used for function approximation and pattern classification with faster convergence and lesser computational complexity than a ...
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Mathematical Model and Algorithm for Link Community Detection in Bipartite Networks
... to functional subunits in the complex sys- tems. In complex network, a node community can be defined as a subgraph induced by a set of nodes, while a link community is a subgraph induced by a set of ...
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Functional Link Artificial Neural Network for Classification Task in Data Mining
... the Functional Link Artificial Neural Network (FLANN) model for the task of pattern classification in data ...FLANN model functionally expands the given set of ...neural network. ...
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Functional link neural network – artificial bee colony for time series temperature prediction
... In this model, the colony of artificial bees consists of three groups, which are employed bees, onlookers and scouts [31]. For each food source there is only one artificial employed bee. The number of employed ...
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