[PDF] Top 20 Artificial Neural Network and Non-Linear Regression: A Comparative Study

Artificial Neural Network and Non-Linear Regression: A Comparative Study

... It has been discussed that the beyond n = 6, the performance of the model on the validation set does not increase any further but the performance on the training data was better. The reason behind this may be that ... See full document

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Comparative Study of Classification Techniques on Breast Cancer FNA Biopsy Data

... The Artificial neural network on the other hand has been determined to be an effective tool in classification though the operations within the network structure are ...as neural ... See full document

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Comparative Study On Effort Estimation Using Different Data Mining Techniques

... work. Artificial Neural Network Algorithm Implementation: This is a supervised approach as the other algorithms in the proposed ...1000. Artificial Neural Network classification ... See full document

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A REVIEW ON DIMENSIONALITY REDUCTION USING COPULA APPROACH IN DATA MINING

... a comparative study of four different classifiers, multiple linear regression (MLR), artificial neural network (ANN), k-nearest neighbor (k-NN), and naive Bayesian ... See full document

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Analysis of Tanzanian Energy Demand using Artificial Neural Network and Multiple Linear Regression

... of artificial neural network (ANN) and multiple linear regression (MLR) ...complex non-linear functions which are the characteristics possessed by energy demand indicators ... See full document

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Computing air demand using the Takagi–Sugeno model for dam outlets

... to study the air demand in low-level outlet ...identify linear and non-linear parameters in the ANFIS ...Levenberg-Marquardt neural network (LMNN) and multiple linear ... See full document

17

Conjugate gradient neural network in prediction of clay behavior and parameters sensitivities

... linear, regression analysis can only be successfully applied if prior knowledge of the nature of the non-linearity ...the non-linearity is not required for artificial neural ... See full document

12

Forecasting nitrate concentration in groundwater using artificial neural network and linear regression models

... using regression and neural ...utilized artificial neural networks to predict the pesticide and nitrate contamination in rural private ...used regression and neural networks to ... See full document

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Application of Artificial Neural Network And Multiple Linear Regression Model for Forecasting of Container Throughput In APM Terminals Apapa Port A Comparative Approach

... this study strives to search among two models, for a model that is capable of generating the most accurate prediction of container throughput useful for Port authorities in a short time which can be achieved ... See full document

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Automatic Pattern Forecasting from Banking Financial Data

... a non-decreasing and differentiable function; the most common choices are either the identity function, as the logistic one y = 1/ (1+e x ...the Linear Regression on the filtered data set, looking at ... See full document

7

Non Linear Text Regression with a Deep Convolutional Neural Network

... an artificial neural network (ANN) for modelling text ...convolutional neural network, inspired by their breakthrough results in image process- ing (Krizhevsky et ...convolution ... See full document

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An Artificial Neural Network Modelling Approach for Development of QSAR Model for Anticancer Activity of Gossypol Acetic Acid against Anticancer Target BCL2

... the study of biological activities with properties or molecular structures which is helpful to explore the relationship between the structures of ligands and their activities ...Multiple Linear ... See full document

10

Implementation of Artificial Neural Network for Short Term Load Forecasting

... methods, regression approaches, fuzzy logic, genetic algorithms, time series methods and artificial neural network ...techniques, artificial neural network is widely used, ... See full document

5

A Review of Price Forecasting Problem and Techniques in Deregulated Electricity Markets

... the linear regression scores over the other reported ...on Artificial Intelligence (AI) were also developed for forecasting of electrical load, such as expert systems, fuzzy inference, fuzzy ... See full document

19

Hole Cleaning Prediction in Foam Drilling Using Artificial Neural Network and Multiple Linear Regression

... complex non- Newtonian mud ...[10-16]. Artificial neural networks (ANNs) are sim- ple and more reliable predictive tools inspired by studies on the human nerve and brain system that can be used to ... See full document

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... Multiple Regression (MR) analysis and MATLAB programming to estimate the required subsoil properties from the measured ...of non-visited locations. Accordingly, [13] compared MRLA and Artificial ... See full document

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Comparative Analysis of Regression based and Supervised Learning Algorithms for Predicting Traffic Noise Levels in Indian Scenario

... the comparative analysis our aim would be to find results obtained by algorithms such as multi linear regression, polynomial regression, artificial neural networks, k-nearest ... See full document

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Comparative Analysis of Multiple Linear Regression and Artificial Neural Network for Predicting Friction and Wear of Automotive Brake Pads Produced from Palm Kernel Shell

... manufacturers and suppliers due to the complex nature of wear mechanisms involved in the system [1]. Thus investigating and coming up with model equations for the evolution of the tribo-system (disc, brake pads) we go a ... See full document

9

A Three-Step Neural Network Artificial Intelligence Modeling Approach for Time, Productivity and Costs Prediction: A Case Study in Italian Forestry

... this study is to analyze how the different harvesting processes affect operational costs and labor productivity in typical small-scale Italian harvesting ...multiple linear regression model (MLR) and ... See full document

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Modeling for Prediction of Characteristic Deflection of Flexible Pavements- Comparison of Models Based on Artificial Neural Network and Multivariate Regression Analysis

... Artificial Neural Networks have the ability to relate between the input data and the corresponding output data which can be defined depending on single or multiple parameters for solving a linear or ... See full document

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