Search Results - Optimized Backpropagation Learning Algorithm

Inversion of Water Quality Parameters from UAV Hyperspectral Data Based on Intelligent Algorithm Optimized Backpropagation Neural Networks of a Small Rural River

Authors: Manqi Wang Caili Zhou Jiaqi Shi et al.

Source: Remote Sensing, Vol 17, Iss 1, p 119 (2025)

Subject Terms: remote sensing, machine learning algorithm, small rural river, Science, UAV hyperspectral images, water quality parameter, environmental monitoring

Access URL: https://doaj.org/article/e26d15d0ad6b4193a6dadd3d423c12ae

Predictive modeling on the mechanical properties of marine coral sand-clay mixtures based on machine learning algorithms and triaxial shear tests

Authors: Yang, Bowen Xu, Kaiwei Liu, Yanqi et al.

Source: Frontiers in Marine Science. 12

Subject Terms: empirical formula, LDA-BPNN model, machine learning, marine coral sand-clay mixture, strength prediction

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-245378
https://doi.org/10.3389/fmars.2025.1630481

A novel hybrid model for species distribution prediction using probabilistic random forest, principal component analysis and genetic algorithm.

Authors: Adekunle, Taiwo A. Ogundoyin, Ibrahim K. Akanbi, Caleb O.

Source: PLoS ONE; 9/10/2025, Vol. 20 Issue 9, p1-21, 21p

Subject Terms: SPECIES distribution, RANDOM forest algorithms, RODENTS, PRINCIPAL components analysis, FEATURE extraction, OPTIMIZATION algorithms, MACHINE learning, GENETIC algorithms

Geographic Terms: NIGERIA

2D Prediction of the Nutritional Composition of Dishes from Food Images: Deep Learning Algorithm Selection and Data Curation Beyond the Nutrition5k Project.

Authors: Bianco, Rachele Coluccia, Sergio Marinoni, Michela et al.

Source: Nutrients. Jul2025, Vol. 18 Issue 13, p2196. 23p.

A Perceptron with Optimized Backpropagation Learning Algorithm to preset a Temper mill machine: NEUROSKIN

Authors: N. Pican P. Bresson F. Alexandre et al.

Contributors: N. Pican P. Bresson F. Alexandre et al.

Source: http://www.cee.hw.ac.uk/~ceenvp/home/Pages/publications/NEURONIMES93.ps.Z.

Subject Terms: MLP, Optimized Backpropagation Learning Algorithm, training

File Description: application/postscript

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.8286; http://www.cee.hw.ac.uk/~ceenvp/home/Pages/publications/NEURONIMES93.ps.Z

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.8286
http://www.cee.hw.ac.uk/~ceenvp/home/Pages/publications/NEURONIMES93.ps.Z

A Perceptron with Optimized Backpropagation Learning Algorithm to preset a Temper mill machine: NEUROSKIN

Authors: Nicolas Pican Patrick Patrick Bresson Frdric Alexandre et al.

Contributors: Nicolas Pican Patrick Patrick Bresson Frdric Alexandre et al.

Source: ftp://ftp.loria.fr/pub/loria/rfia/publications/cortex/pican.Perceptron-Temper_Mill93.ps.Z

Subject Terms: MLP, Optimized Backpropagation Learning Algorithm

File Description: application/postscript

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.468

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.468

An archimedes optimization algorithm based extreme gradient boosting model for predicting the bending strength of UV cured glass fiber reinforced polymer composites

Authors: Zhang, Xi Xia, Yangyang Zhang, Chao et al.

Source: Polymer Composites.

Subject Terms: Archimedes optimization algorithm, bending strength prediction, machine learning, sensitivity analysis, UV-GRFP composites

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-245638

Smart Cushions with Machine Learning-Enhanced Force Sensors for Pressure Injury Risk Assessment

Authors: Xinhao Xiang Ke Zhang Yi Qin et al.

Source: ACS Applied Materials & Interfaces. 16:38466-38477

Subject Terms: Pressure Ulcer, Machine Learning, Pressure, Humans, Buttocks, Neural Networks, Computer, Risk Assessment, Algorithms

Access URL: https://pubmed.ncbi.nlm.nih.gov/38995996

Towards The Deep Semantic Learning Machine Neuroevolution Algorithm: An exploration on the CIFAR-10 problem task

Authors: Hofman, Olivier Jean Marie Gonçalves, Ivo Carlos Pereira Castelli, Mauro et al.

Contributors: Hofman, Olivier Jean Marie Gonçalves, Ivo Carlos Pereira Castelli, Mauro et al.

Subject Terms: Supervised Machine Learning, Deep Learning, Convolutional Neural Networks, Neuroevolution, Deep Semantic Learning Machine, Aprendizado Automático Supervisionada, Aprendizado Profundo, Rede Neural Convolucional, Neuroevolução

File Description: application/pdf

Availability: http://hdl.handle.net/10362/118581

Optimization of Millet Malting Parameters Using Artificial Neural Network and Response Surface Methodology.

Authors: Erfaniannejad Hosseini Nabadou, Fatemeh Moghimi, Masoumeh Tahmasebi, Aminallah et al.

Source: Food Science & Nutrition; May2025, Vol. 13 Issue 5, p1-13, 13p

Subject Terms: ARTIFICIAL neural networks, MACHINE learning, MALTING, RESPONSE surfaces (Statistics), TRANSFER functions

Design and Simulation of a Multilayer Chemical Neural Network That Learns via Backpropagation.

Authors: Lakin, Matthew R.

Source: Artificial Life; Summer2023, Vol. 29 Issue 3, p308-335, 28p

Subject Terms: FEEDFORWARD neural networks, MACHINE learning, WET chemistry, CHEMICAL reactions, DNA nanotechnology, PROGRAMMING languages, TRANSFER functions

Method for Identifying and Analyzing Factors Influencing Traffic Efficiency at Lane Level.

Authors: Huasheng Liu Kui Dong Kai Ding et al.

Source: IAENG International Journal of Computer Science. Jul2025, Vol. 52 Issue 7, p2163-2186. 24p.

Subject Terms: Computer network traffic, Travel time (Traffic engineering), City traffic, Elasticity (Economics), Machine learning

Optimization of type-2 fuzzy weights in backpropagation learning for neural networks using GAs and PSO.

Authors: Gaxiola, Fernando Melin, Patricia Valdez, Fevrier et al.

Source: Applied Soft Computing. Jan2016, Vol. 38, p860-871. 12p.

Subject Terms: Mathematical optimization, Soft sets, Back propagation, Machine learning, Artificial neural networks, Particle swarm optimization

A Fast Semi-linear Backpropagation Learning Algorithm.

Authors: Hutchison, David Kanade, Takeo Kittler, Josef et al.

Source: Artificial Neural Networks - ICANN 2007 (978-3-540-74689-8); 2007, p190-198, 9p

Dynamic adaptation of the PID's gains via Interval type-1 non-singleton type-2 fuzzy logic systems whose parameters are adapted using the backpropagation learning algorithm.

Authors: Méndez, Gerardo M. Montes Dorantes, P. Noradino Alcorta, M. Aracelia

Source: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Jan2020, Vol. 24 Issue 1, p17-40, 24p

Subject Terms: FUZZY logic, FUZZY systems, MACHINE learning, STANDARD deviations, PRODUCTION standards, PID controllers, PHYSIOLOGICAL adaptation

A BRBES to Support Diagnosis of COVID-19 Using Clinical and CT Scan Data

Authors: Shafkat Raihan, S.M. Islam, Raihan Ul Hossain, M. S. et al.

Source: Proceedings of the International Conference on Big Data, IoT, and Machine Learning Lecture Notes on Data Engineering and Communications Technologies. :483-496

Subject Terms: Biomimetics, Computerized tomography, Deep learning, Diseases, Expert systems, Genetic algorithms, Patient treatment, SARS, Belief rule-based expert system, Belief rules, BRBES-based adaptive differential evolution, COVID-19 diagnose, CT-scan, Diagnosis methods, Differential Evolution, Hematological data, Rule-based expert system, Scan data, Diagnosis, Pervasive Mobile Computing, Distribuerade datorsystem

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-88522
https://doi.org/10.1007/978-981-16-6636-0_37

An optimized backpropagation neural network models for the prediction of nanomaterials concentration for purification industrial wastewater.

Authors: Hassanien, Aboul Ella Abouelmagd, Lobna M. Mahmoud, Amira S. et al.

Source: Engineering Applications of Artificial Intelligence. Nov2023:Part C, Vol. 126, pN.PAG-N.PAG. 1p.

Subject Terms: *ARTIFICIAL neural networks, *SEWAGE, *INDUSTRIAL wastes, *INDUSTRIAL concentration, *OPTIMIZATION algorithms, *COLOR removal (Sewage purification)

A study on a low power optimization algorithm for an edge-AI device

Authors: Itaru Hida Kentaro Orimo Masato Motomura et al.

Source: Nonlinear Theory and Its Applications, IEICE. 2019, 10(4):373

Design of highly effective multilayer feedforward neural network by using genetic algorithm.

Authors: Üstün, Oğuz Bekiroğlu, Erdal Önder, Mithat

Source: Expert Systems; Aug2020, Vol. 37 Issue 4, p1-19, 19p

Subject Terms: FEEDFORWARD neural networks, GENETIC algorithms, MULTILAYER perceptrons, MACHINE learning, NETWORK performance

Plate Recognition Using Backpropagation Neural Network and Genetic Algorithm.

Authors: Tarigan, Joseph Nadia, null Diedan, Ryanda et al.

Source: Procedia Computer Science. 2017, Vol. 116, p365-372. 8p.

Subject Terms: Image recognition (Computer vision), Automobile license plates, Back propagation, Genetic algorithms, Automobile parking, Artificial neural networks, Management