# [PDF] Top 20 Fuzzy nonlinear regression using artificial neural networks

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### Fuzzy nonlinear regression using artificial neural networks

... Abstract: **Fuzzy** linear **regression** analysis with symmetric triangular **fuzzy** number coefficient has been introduced by Tanaka et ...the **fuzzy** **nonlinear** **regression** **using** ... See full document

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### Egg Hatchability Prediction by Multiple Linear Regression and Artificial Neural Networks

... The **artificial** **neural** network (ANN), an **artificial** intelligence technique, is a potential tool for modeling data in poultry ...of **using** ANN methodology to estimate production parameters of ... See full document

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### Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

... an **artificial** NN approach for **nonlinear** modelling of multivariate streamflow ...series **using** multi-layer feed- forward error-backpropagation NN, with iterated multi-step prediction, where the single ... See full document

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### Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

... techniques **using** the same input data, and the results illustrated the importance of terrain roughness and soil type as key factors within the model; **using** only these two variables, the analysis returned a ... See full document

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### Spatial predictive mapping using artificial neural networks

... Advangeo® provides the software environment for effective data pre-processing, step-by-step model generation, and result visualisation. It is a tool to build up structured and comprehensible models within the widely used ... See full document

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### RegnANN: Reverse Engineering Gene Networks using Artificial Neural Networks.

... Once the ensemble is trained, the topology of the gene regulatory network is obtained by applying a second procedure. Considering each gene in the network separately, we pass a value of 1 to the input neuron of the ... See full document

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### Masonry Compressive Strength Prediction Using Artificial Neural Networks

... highly **nonlinear** relation between the compressive strength of masonry and the geometrical and mechanical properties of the components of the ...ﬁcial **neural** **networks** for predicting the compressive ... See full document

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### Predicting the Effects of Medical Waste in the Environment Using Artificial Neural Networks: A Case Study

... Jordan **using** **Artificial** **Neural** **Networks** (ANNs) ...Generalized **Regression** **Neural** Network (GRNN) is used to predict the diseases ...largest **regression** value affect the acute ... See full document

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### RECENT METHODS FOR OPTIMIZATION OF PLASTIC INJECTION MOLDING PROCESS –A RETROSPECTIVE AND LITERATURE REVIEW

... a **fuzzy** **neural** network-based in-process mixed material- caused flash prediction (FNN-IPMFP) system for injection molding ...a **fuzzy** **neural** network to predict flash in injection molding ... See full document

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### Forecasting Short Term Electricity Price Using Artificial Neural Network and Fuzzy Regression

... Now **using** **fuzzy** **regression** which is clarified before, the price of electricity is ...perform **fuzzy** **regression** the input variables should be indicated, here the input variables are the ... See full document

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### J. Braz. Chem. Soc. vol.26 número1

... extraction **using** a minicolumn packed with Amberlite XAD-4 modified with 3,4-dihydroxybenzoic ...optimized **using** Doehlert ...squares **regression** and **artificial** **neural** **networks**) ... See full document

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### Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks

... **Artificial** **neural** **networks** (ANNs), as one of the most attractive branches in **artificial** intelligence, has the potential to handle problems such as modeling, estimating, prediction, ... See full document

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### Land Cover Classification from Multispectral Data Using Computational Intelligence Tools: A Comparative Study

... **Artificial** **Neural** **Networks** (ANN) form a classification technique where neurons are trained to detect patterns in the training dataset and then the trained classifier is applied to unknown ...and ... See full document

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### PREDICTION OF HYDRODYNAMIC COEFFICIENTS OF PERMEABLE PANELED BREAKWATER USING ARTIFICIAL NEURAL NETWORKS

... In this study the most common **neural** network type, the multilayer perceptron, was adopted. This type of network is formed by three or more layers of basic computing units named **artificial** neurons or nodes. ... See full document

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### Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

... An ANN is a system inspired by the operation of biological neurons with the purpose of learning a certain system. The construction of an ANN is achieved by providing a stimu- lus to the neuronal model, calculating the ... See full document

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### Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran

... in **artificial** and **fuzzy** **neural** **networks** technique has been conducted to separate classes of forest from non-forest **using** SPOT satellite **neural** network method with the accuracy of ... See full document

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### Bol. Ciênc. Geod. vol.23 número1

... Coordinate transformation is necessary in the surveying and mapping industry particularly in developing countries like Ghana where the non-geocentric datum which is still utilized is highly heterogeneous. It also creates ... See full document

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### Design of an Omni-directional Spherical Robot: Using Fuzzy Control

... stabilization **fuzzy** controller of the spherical mobile robot is ...five **fuzzy** sets for each input variable then there are 625 **fuzzy** rules in this **fuzzy** ...the **fuzzy** implication but also ... See full document

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### Prediction of Operating Characteristics of Electrotechnical Devices using Artificial Neural Networks

... appropriate **neural** network, able to simulate the behavior of proximity sensor at different functioning conditions, we choose a high degree of parameterization for the application, with different kind of ... See full document

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### Modeling Distillation Column Using ARX Model Structure and Artificial Neural Networks

... [r] ... See full document

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