Results 21 to 30 of about 265,148 (311)

Radial Basis Function Neural Network Model for Dissolved Oxygen Concentration Prediction Based on an Enhanced Clustering Algorithm and Adam

IEEE Access, 2021
In fishery aquaculture, water quality directly determines the economic benefits of aquatic products, and dissolved oxygen is an important factor affecting water quality.
Dashe Li, Xueying Wang, Jiajun Sun, Yanli Feng   +3 more
doaj   +1 more source

Radial basis function network based on time variant multi-objective particle swarm optimization for medical diseases diagnosis [PDF]

, 2011
This paper proposes an adaptive evolutionary radial basis function (RBF) network algorithm to evolve accuracy and connections (centers and weights) of RBF networks simultaneously.
Qasem, Sultan Noman, Shamsuddin, Siti Mariyam   +1 more
core   +1 more source

Radial Basis Function Networks for Conversion of Sound Spectra

EURASIP Journal on Advances in Signal Processing, 2001
In many advanced signal processing tasks, such as pitch shifting, voice conversion or sound synthesis, accurate spectral processing is required. Here, the use of Radial Basis Function Networks (RBFN) is proposed for the modeling of the spectral changes ...
Carlo Drioli
doaj   +1 more source

Human action recognition using time delay input radial basis function networks [PDF]

, 2014
This paper presents a fast, vision-based method for the problem of human action representation and recognition. The first problem is addressed by constructing an action descriptor from spatiotemporal data of action silhouettes based on appearance and ...
Abdul Halin, Izhal, Aris, Ishak, Kalhor, Davood, Moaini, Trifa   +3 more
core   +1 more source

Organisms modeling: The question of radial basis function networks

ITM Web of Conferences, 2014
There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are ...
Muzy Alexandre, Massardier Lauriane, Coquillard Patrick   +2 more
doaj   +1 more source

Tourism demand forecasting with neural network models : Different ways of treating information [PDF]

, 2014
This paper aims to compare the performance of three different artificial neural network techniques for tourist demand forecasting: a multi-layer perceptron, a radial basis function and an Elman network.
Clavería González, Óscar, Monte Moreno, Enric, Torra Porras, Salvador   +2 more
core   +2 more sources

Equalizer Design: HBOA-DE-trained radial basis function neural networks

Egyptian Informatics Journal
Communication systems that rely on wireless technology require signal processing techniques to improve their channel performance. Wireless communications are susceptible to various signal distortions during transmission, including inter-symbol ...
Santosh Kumar Das, Satya Ranjan Pattanaik, Pradyumna Kumar Mohapatra, Saroja Kumar Rout, Abdulaziz S. Almazyad, Muhammed Basheer Jasser, Guojiang Xiong, Ali Wagdy Mohamed   +7 more
doaj   +1 more source

Statistical Analysis of Novel Ensemble Recursive Radial Basis Function Neural Network Performance on Global Solar Irradiance Forecasting

Journal of Electrical and Computer Engineering, 2023
Reliable operation of energy management systems, grid stability, and managing energy demand responses are becoming challenging because of the flickering nature of solar irradiance.
Manoharan Madhiarasan, Mohamed Louzazni, Brahim Belmahdi   +2 more
doaj   +1 more source

Network Intrusion Detection Based on Extended RBF Neural Network With Offline Reinforcement Learning

IEEE Access, 2021
Network intrusion detection focuses on classifying network traffic as either normal or attack carrier. The classification is based on information extracted from the network flow packets.
Manuel Lopez-Martin, Antonio Sanchez-Esguevillas, Juan Ignacio Arribas, Belen Carro   +3 more
doaj   +1 more source

A Divide-and-Cooperate Machine Learning Model-Based RBF With Its VC Dimension Analysis

IEEE Access, 2020
In this paper, a Divide-and-Cooperate Machine Learning Model (DCML) based Radial Basis Function Network (RBF) is constructed. This DCML is composed of several sub-RBF networks that take some variables as their inputs. The output of DCML is the sum of sub-
Rongbo Huang, Jianwei Dong, Suixun Guo, Yanmei Chen   +3 more
doaj   +1 more source