[PDF] Top 20 Artificial Neural Network Learning Techniques: A Survey

Artificial Neural Network Learning Techniques: A Survey

... This algorithm is involved in removing redundancy in data sets and features. It is accomplished using a principle variable. The features are selected and extracted using various techniques involved in their ... See full document

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ADAPTIVE COLOR FILTER ARRAY INTERPOLATION ALGORITHM BASED ON HUE TRANSITION AND EDGE DIRECTION

... examples stored in the system can be reduced to only 2–4% of the original database without a decrease in the diagnostic performance and algorithms based random mutation hill climbing provides the best balance between the ... See full document

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Estimation of Punching Shear Capacity of Concrete Slabs Using Data Mining Techniques

... 2. Artificial Neural Networks (ANN) The ANN is an artificial intelligence based approach generally used for the exact forecast of civil engineering problems [36, ... See full document

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Comparative Analysis of ANN-ICA and ANN-GWO for Crop Yield Prediction

... MACHINE LEARNING METHODS As it is mentioned above, in this study, the performance of two hybrid machine learning methods in the crop yield prediction is ...machine learning in prediction ...of ... See full document

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A Review on Heart Disease Prediction using Machine Learning and Data Analytics Approach

... machine learning techniques are used to predict the heart disease, such as Artificial Neural Network (ANN), Decision tree, Fuzzy Logic, K-Nearest Neighbour(KNN), Naïve Bayes and Support ... See full document

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Machine Learning and Deep Learning

... A Deep Neural Network consists of an input layer, severalhidden layers, and an output layer. Each layer includes severalunits called neurons. These neurons are also called as artificial neurons. A ... See full document

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Predictive Analytics: A Review of Trends and Techniques

... computer techniques, newer techniques have been developed and better and better algorithms been introduced over the period of ...of artificial intelligence and machine learning have changed ... See full document

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Wheat Yield Prediction Using Artificial Neural Network and Crop Prediction Techniques (A Survey)

... Artificial neural networks, which are nonlinear data-driven approaches as opposed to the above model-based nonlinear methods, are capable of performing nonlinear modeling without a priori knowledge about ... See full document

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A Survey on Rainfall Prediction using Artificial Neural Network

... powerful techniques based on ...using Artificial Neural Networks based on feed-forward back- propagation ...three Neural Network models: a one-day- ahead model for predicting the ... See full document

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HYBRID AND INTEGRATED APPROACH TO SHORT TERM LOAD FORECASTING

... of artificial intelligence techniques to the Load-Forecasting ...Various Artificial Intelligence (AI) techniques used for load forecasting are Expert systems, Fuzzy, Genetic Algorithm, ... See full document

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Survey on Recent Algorithms for Privacy Preserving Data mining S.Selva Rathna #1 , Dr. T. Karthikeyan *2

... of techniques have been proposed for modifying or transforming data to preserve privacy which are effective without compromising ...detailed survey on recent algorithms developed for achieving Privacy ... See full document

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Role of Artificial Neural Network in Welding Technology: A Survey

... the neural network approach is more better than that conventional regression analysis[1] because Neural network based approach can carry out interpolation with in the a ...propagation ... See full document

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Implementation of Neural Network Back Propagation Training Algorithm on FPGA

... multilayer artificial neural network is studied and successfully implemented on ...of neural networks on FPGA than training in computer system and make a trainable neural network ... See full document

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Comparison of Decision Tree and ANN Techniques for Data Classification

... The data used for this research is the pupil data of computer science department [2]. The information such as age, gender, religion, country, academic details such as institution last studied, course taken, course ... See full document

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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 ... See full document

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Application of Artificial Intelligence for Epilepsy Disease

... deep learning architectures, for example deep generative models [9] [10] and recurrent Neural Network (RNN) ...belief network [11] and restricted Boltzmann machine [10], in short it is written ... See full document

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Survey on Credit Card Fraud Detection Methods

... and Neural network approach is automatic credit card fraud detection system and type of artificial intelligence programming which is based on variety of methods including machine learning ... See full document

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DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY USING ADAPTIVE BOOSTING AND ARTIFICIAL NEURAL NETWORK

... Probabilistic Neural Network (PNN) and Support Vector Machine were used to diagnosis ...convolutional neural networks in order to segment the blood ...deep learning based computer-aided system ... See full document

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Comparison of Accuracy of Artificial Neural Network (ANN) and Kriging Methods for Estimating Chlorine Concentration

... and artificial neural network as interpolating techniques to find the best method by which estimating the spatial variations of the chlorine ... See full document

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Image Compression Techniques Using Artificial Neural Network

... Image compression focuses on the problem of reducing the amount of data required to represent a digital image. The process of reducing the image for image storage requirements of representation of an image. Compression ... See full document

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