Artificial neural network methods
Informative Feature Trained Classification System For Credit Card Fraud Detection
... Neural network based fraud detection methods are most ...of artificial neurons is contained in artificial neural ...of neural network. In neural ...
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Co-simulation framework for on-chip LiDAR sensors in a cyber-physical system
... sensor network by using SCANeR. The second module with three specific Artificial Intelligence-based methods ...(i.e., artificial neural network, self-organized map and support ...
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Classification and Prediction on Rural Property Mortgage Data with Three Data Mining Methods
... mining methods that can be used to study these specific problems [4] ...learning methods (Bayesian network and Artificial neural network) and one statistical technique (Logistic ...
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ABSTRACT: Chaos and chaos control are new theories and new fields of nonlinear dynamics. Chaotic motion
... Artificial neural network has been proved to have the characteristics of arbitrary approximation to nonlinear ...Combining artificial neural network with chaotic system, some ...
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An Efficient Segmentation Approach with Texture Analysis for Plant Disease Identification in CIELAB Space
... regression, artificial neural network (back spread neural network, summed up regression neural network) and bolster vector machine (SVM) was ...division methods to ...
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Comparison of Artificial Intelligence Techniques for river flow forecasting
... of Artificial Intelligence methods is be- coming increasingly common in the modeling and forecast- ing of hydrological and water resource ...and Artificial Neural Network (ANN) ...
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Radio location of partial discharge sources : a support vector regression approach
... a network of inexpensive radio sensors to sample the spatial patterns of PD received signal ...of artificial neural network (ANN) ...LSSVR methods are superior to ANNs in ...
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Rainfall-runoff modelling using artificial neural network method
... of neural networks is an extremely interdisciplinary field such as science, engineering, automotive, aerospace, banking, medical, business, transportation, defense, industrial, telecommunications, insurance, and ...
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Artificial Neural Network Approaches to the Prediction of Eutrophication and Algal Blooms in Aras Dam, Iran
... and Methods: In this study, artificial neural network (ANN) model was investigated to predict the chlorophyll-a (Chl-a) concentration in water of dam ...
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Estimation of groundwater level using a hybrid genetic algorithm-neural network
... of neural networks, which is utilized in the most frequently mentioned studies for aquifers ...forward neural network; therefore, numerical weights of neuron connections and biases represent the ...
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Using Artificial Neural Network Modeling in Forecasting Revenue: Case Study in National Insurance Company/Iraq
... in methods of stock evaluation; and in most of these cases, it is a fun- damental factor in investing in the stock ...“artificial neural network with an error backward propagation algorithm” ...
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Application of Artificial Intelligence for Epilepsy Disease
... Deep learning is a precise structure of the group of machine learning methods. Deep learning is a precise structure of depiction- based learning, where a system assimilates and forms fundamental aspects from each ...
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Evaluation of different techniques for generating landslide susceptibility map
... summary, methods are a bridge between devices and ...and methods are also considered as algorithms (Melchiorre et ...employs methods such as the logistic and spatial regressions, Geographically ...
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INFORMATION TECHNOLOGY FOR NUMERICAL SIMULATION OF CONVECTIVE FLOWS OF A VISCOUS INCOMPRESSIBLE FLUID IN CURVILINEAR MULTIPLY CONNECTED DOMAINS
... the network is determined by the routing algorithm [5]. Besides network accounting and monitoring, system administrators can identify various problems that may occur in the ...for network flow ...
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Application of smart spectrophotometric methods and artificial neural network for the simultaneous quantitation of olmesartan medoxamil, amlodipine besylate and hydrochlorothiazide in their combined pharmaceutical dosage form
... Artificial neural network (ANN) is a type of artificial intelligence method that resembles biological nervous system in having the ability to find the relationship be- tween inputs and ...
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Title: CLASSIFICATION ON BREAST CANCER USING GENETIC ALGORITHM TRAINED NEURAL NETWORK
... Metaheuristic methods for training neural networks are based on local search, population methods, and others such as cooperative coevolutionary models ...an Artificial Bee Colony (ABC) ...
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Title: DIAGNOSIS ON LUNG CANCER USING ARTIFICIAL NEURAL NETWORK
... In neural networks metaheuristic methods are based on local searches, population and other methods, such as cooperative models ...the Artificial bee colony (ABC) to develop an ANN with two ...
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Comparison of Artificial Intelligence Methods on the Example of Tea Classification Based on Signals from E nose Sensors
... radial neural networks (PNN and RBF) and fuzzy logic (ANFIS and FUZZY) obtained the best results in accuracy criteria, as they always classified all kinds of tea ...FF network exhibits greater stability ...
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Beat classification of an ecg signal using photoplethysmography and neural network
... extraction methods, namely wavelet decomposition, and probabilistic neural network ...extraction methods. ECG images classification using artificial neural network based ...
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Comparative Analysis of ANN-ICA and ANN-GWO for Crop Yield Prediction
... learning methods artificial neural network imperialist competitive algorithm and artificial neural network gray wolf ...learning methods is evaluated, and results ...
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