Results 271 to 280 of about 9,482,218 (334)

A novel artificial intelligence approach based on Multi-layer Perceptron Neural Network and Biogeography-based Optimization for predicting coefficient of consolidation of soil

CATENA, 2019
Coefficient of consolidation (Cv) is a measure of compressibility of soil. This coefficient is an important parameter which is used in the design of foundation of civil engineering structures and also in the slope stability analysis.
B. Pham, M. D. Nguyen, Kien-Trinh Thi Bui, Indra Prakash, K. Chapi, D. Bui   +5 more
semanticscholar   +1 more source

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Journal of Loss Prevention in the Process Industries, 2016
Karim Salahshoor, Morteza Zadkarami, Mehdi Shahbazian   +2 more
exaly   +2 more sources

Analysis of hidden nodes for multi-layer perceptron neural networks

Pattern Recognition, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Long-Wen Chang
exaly   +2 more sources

Estimation of effective connectivity using multi-layer perceptron artificial neural network [PDF]

Cognitive Neurodynamics, 2017
Studies on interactions between brain regions estimate effective connectivity, (usually) based on the causality inferences made on the basis of temporal precedence. In this study, the causal relationship is modeled by a multi-layer perceptron feed-forward artificial neural network, because of the ANN's ability to generate appropriate input-output ...
Ali Motie Nasrabadi, Nasibeh Talebi
exaly   +3 more sources

Statistical modelling of artificial neural networks using the multi-layer perceptron

Statistics and Computing, 2003
Multi-layer perceptrons (MLPs), a common type of artificial neural networks (ANNs), are widely used in computer science and engineering for object recognition, discrimination and classification, and have more recently found use in process monitoring and control.
Aitkin M, Foxall R
openaire   +3 more sources

Simulation of CO 2 capture using sodium hydroxide solid sorbent in a fluidized bed reactor by a multi-layer perceptron neural network

Journal of Natural Gas Science and Engineering, 2016
Shahrokh Shahhosseini, Ahad Ghaemi
exaly   +2 more sources

Assembling engineering knowledge in a modular multi-layer perceptron neural network

Proceedings of International Conference on Neural Networks (ICNN'97), 2002
The popular multi-layer perceptron (MLP) topology with an error-back propagation learning rule doesn't allow the developer to use the (explicit) engineering knowledge as available in real-life problems. Design procedures described in literature start either with a random initialization or with a 'smart' initialization of the weight values based on ...
Jansen, WJ, Diepenhorst, M, Nijhuis, JAG, Spaanenburg, L   +3 more
openaire   +3 more sources

Exploratory test oracle using multi-layer perceptron neural network

2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2016
In the context of exploratory testing (ET), human knowledge and intelligence is applied as a test oracle. The exploratory tester designs and executes the tests on fly and compares the actual output produced by the application under test with the expected output in the testers' mind.
Wellington Makondo, Raghava Nallanthighal, Innocent Mapanga, Prudence Kadebu   +3 more
openaire   +2 more sources

Prediction of soil compression coefficient for urban housing project using novel integration machine learning approach of swarm intelligence and Multi-layer Perceptron Neural Network

Advanced Engineering Informatics, 2018
In many engineering projects, the soil compression coefficient is an important parameter used for estimating the settlement of soil layers. The common practice of determining the soil compression coefficient via the oedometer test is time-consuming and ...
D. Bui, Viet-Ha Nhu, Nhat-Duc Hoang
semanticscholar   +1 more source

Multi-layer Perceptron Neural Networks in Geospatial Analysis

2012
Geospatial analysis involves using a variety of approaches. Deciding on a suitable approach depends on the complexity of the problem being addressed and the degree to which the problem is understood. Several algebraic and numerical computing techniques can be used to describe the behavior and nature of real geographical processes and develop ...
Duong Dang Khoi, Yuji Murayama
openaire   +1 more source