Results 281 to 290 of about 9,482,218 (334)

Solar air heaters performance prediction using multi-layer perceptron neural network– A systematic review

Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2021
In solar thermal systems, solar air heater (SAH) is an important device for heating air using energy of the sun. The solar collector is the most important part of SAH which collects solar radiations as thermal energy (heat) and transmits it to the air ...
Harish Kumar Ghritlahre, Manoj Verma
semanticscholar   +1 more source

Multi-Layer Perceptron Neural Network and nearest neighbor approaches for indoor localization

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2014
Most range-free techniques for indoor localization depend on the received signal strength (RSS) fingerprints. Their performances are relied to the structure of the considered indoor environments. We consider in this paper RSS-based methods: Multi-Layer Perceptron Neural Network (MLPNN), and K-nearest neighbor (KNN), and compare their performance under ...
Dakkak, M., Daachi, B., Nakib, Amir, Siarry, P.   +3 more
openaire   +2 more sources

Modelling land use/land cover changes prediction using multi-layer perceptron neural network (MLPNN): a case study in Makassar City, Indonesia

, 2020
This study used Remote Sensing and Geographic Information System (GIS) tools to produce a predictive model of land use/land cover changes in Makassar City by 2031.
Andi Muhammad Yasser Hakim, S. Baja, D. A. Rampisela, S. Arif   +3 more
semanticscholar   +1 more source

Fault tolerant capability of multi-layer perceptron neural network

Proceedings of Twentieth Euromicro Conference. System Architecture and Integration, 2002
Mean squared error is the only criteria of backpropagation training to be optimized. Some other good properties of neural networks such as generalization and fault tolerance are only be taken as side effects of neural networks. In this paper we define another energy term called constraint energy to be optimized.
W.S. Hsieh, B.Y. Sher
openaire   +1 more source

An integrated framework of genetic network programming and multi-layer perceptron neural network for prediction of daily stock return: An application in Tehran stock exchange market

Applied Soft Computing, 2019
Evolutionary algorithms are generally used to find or generate the best individuals in a population. Whenever these algorithms are applied to agent systems, they will lead to optimal solutions.
R. Ramezanian, Arsalan Peymanfar, S. B. Ebrahimi   +2 more
semanticscholar   +1 more source

Multi Layer Perceptron Neural Networks Decoder for LDPC Codes

2009 5th International Conference on Wireless Communications, Networking and Mobile Computing, 2009
A very important and near optimum group of the block codes that have been developed in direction of Shannon's theory concept, is low density parity check (LDPC) code. There have been presented different algorithms for decoding of this class of code such as maximum likelihood (ML), bit flipping (BF), a posteriori probability (APP) and sum product (SP ...
A. R. Karami, M. Ahmadian Attari, H. Tavakoli   +2 more
openaire   +1 more source

Effective Detection of GNSS Spoofing Attack Using A Multi-Layer Perceptron Neural Network Classifier Trained by PSO

International Computer Society of Iran Computer Conference, 2020
Global Navigation Satellite System (GNSS) receivers are affected by diverse interactions from various radio frequency transmitters, either intentional or unintentional.
S. Tohidi, M. Mosavi
semanticscholar   +1 more source

Limitations of multi-layer perceptron networks - steps towards genetic neural networks

Parallel Computing, 1990
Abstract In this paper we investigate multi-layer perceptron networks in the task domain of Boolean functions. We demystify the multi-layer perceptron network by showing that it just divides the input space into regions constrained by hyperplanes. We use this information to construct minimal training sets.
openaire   +1 more source

Comparison of Multi Layer Perceptron and Jordan Elman Neural Networks for Diagnosis of Hypertension

Intelligent Automation & Soft Computing, 2014
In this study, from 150 individuals over the age of 30 taken no drugs, sex, age, height, weight, HDL, LDL, Triglyceride, smoking and uric acid were measured. 65 of them are normal but 85 consist of the patients. This data was transferred to the computer by processing methods of quantitative analysis. Data obtained of each patient was applied Artificial
Fuat Türk, Necaattin Barisçi, Aydin Çiftçi, Yakup Ekmekçi   +3 more
openaire   +2 more sources

Classification of plantar foot alterations by fuzzy cognitive maps against multi-layer perceptron neural network

, 2020
Load distribution analysis on foot surface allows knowing human mechanical behavior and aids the doctor in the detection of gait disorders like, the risk of foot ulcerations, leg discrepancy, and footprint alterations. Plantar pressure data combined with
J. Ramirez-Bautista, J. Huerta-Ruelas, L. Kóczy, Miklós F. Hatwágner, Silvia L. Chaparro-Cárdenas, A. Hernández-Zavala   +5 more
semanticscholar   +1 more source