Suchergebnisse - multilayer perceptron AND its stacking integration algorithm

Computational evaluation using machine learning for analysis of membrane desalination process powered by solar energy.

Autoren: Alanazi, Muteb Alharby, Tareq Nafea

Quelle: Scientific Reports; 10/17/2025, Vol. 15 Issue 1, p1-12, 12p

Schlagwörter: MACHINE learning, SALINE water conversion, ENSEMBLE learning, SOLAR energy, ESTIMATION theory, OPTIMIZATION algorithms, MASS transfer

Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints.

Autoren: Lei, Daxing Zhang, Yaoping Lu, Zhigang et al.

Quelle: Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 13, p7097, 20p

Schlagwörter: SHEAR strength, MULTILAYER perceptrons, OPTIMIZATION algorithms, ENSEMBLE learning, ROCK deformation

A Physics-Informed Neural Network Integration Framework for Efficient Dynamic Fracture Simulation in an Explicit Algorithm.

Autoren: Wan, Mingyang Pan, Yue Zhang, Zhennan

Quelle: Applied Sciences (2076-3417); Oct2025, Vol. 15 Issue 19, p10336, 15p

Schlagwörter: MACHINE learning, NUMERICAL integration, ALGORITHMS, CRACK propagation, STRAINS & stresses (Mechanics), SYSTEM integration, MECHANICAL efficiency

A Robust Stacking-Based Ensemble Model for Predicting Cardiovascular Diseases.

Autoren: Bihri, Hayat Charaf, Lalla Amina Azzouzi, Salma et al.

Quelle: AI; Jul2025, Vol. 6 Issue 7, p160, 21p

Schlagwörter: CARDIOVASCULAR diseases, ENSEMBLE learning, SUPPORT vector machines, FORECASTING, DEEP learning, RANDOM forest algorithms, MACHINE learning

A Modular and Explainable Machine Learning Pipeline for Student Dropout Prediction in Higher Education.

Autoren: Bettahi, Abdelkarim Belouadha, Fatima-Zahra Harroud, Hamid

Quelle: Algorithms; Oct2025, Vol. 18 Issue 10, p662, 31p

Schlagwörter: MACHINE learning, HIGHER education, ORGANIZATIONAL governance, TREND analysis, BOOSTING algorithms, SCHOOL dropouts, DATA integration, RESPONSIBILITY

Daily Reservoir Evaporation Estimation Using MLP and ANFIS: A Comparative Study for Sustainable Water Management.

Autoren: Dökmen, Funda Coşkun Dilcan, Çiğdem Ahi, Yeşim

Quelle: Water (20734441); Sep2025, Vol. 17 Issue 17, p2623, 14p

Schlagwörter: WATER management, EVAPORATION (Meteorology), FUZZY neural networks, HYDROMETEOROLOGY, MULTILAYER perceptrons, ARTIFICIAL intelligence, WATER conservation

Machine learning-based prediction of surface roughness and machinability in heat-treated Ni–Cr–Mo low-alloy steels.

Autoren: Behera, Arun Kumar Anand, Abhinav Krishna, Ram

Quelle: Journal of Applied Physics; 10/28/2025, Vol. 138 Issue 16, p1-15, 15p

Schlagwörter: LOW alloy steel, MACHINE learning, SURFACE roughness, NICKEL-chromium alloys, FRACTURE toughness

Development of the artificial neural network's swarm-based approaches predicting East Azerbaijan landslide susceptibility mapping.

Autoren: Sun, Yesen Dai, Hong-liang Xu, Lei et al.

Quelle: Environment, Development & Sustainability; Mar2025, Vol. 27 Issue 3, p6065-6102, 38p

Schlagwörter: METAHEURISTIC algorithms, ARTIFICIAL neural networks, OPTIMIZATION algorithms, LANDSLIDE hazard analysis, RECEIVER operating characteristic curves, LANDSLIDES, MULTILAYER perceptrons

Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach.

Autoren: Hussain, Khadim Mehmood, Kaleem Yujun, Sun et al.

Quelle: Annals of GIS; Sep2025, Vol. 31 Issue 3, p473-500, 28p

Schlagwörter: LAND use, LAND cover, ENVIRONMENTAL impact analysis, ARTIFICIAL neural networks, SUSTAINABLE development, MULTILAYER perceptrons, MACHINE learning, REMOTE sensing

A New RF-MLP Framework Using Stacking Technique for Financial Fraud Detection.

Autoren: Merdas, Hussam Mezher

Quelle: Journal of Engineering Science & Technology Review; 2025, Vol. 18 Issue 2, p116-119, 4p

Schlagwörter: BOOSTING algorithms, FRAUD, RANDOM forest algorithms, DEEP learning, FRAUD investigation

Enhanced fish species classification using dynamic multilayer perceptron and transformer encoders with extra distribution data.

Autoren: Chen, Mei-Hsin Lai, Ting-Hsuan Chen, Yao-Chung et al.

Quelle: Multimedia Tools & Applications; Sep2025, Vol. 84 Issue 31, p37671-37700, 30p

Schlagwörter: CLASSIFICATION of fish, GEOSPATIAL data, MULTILAYER perceptrons, IMAGE recognition (Computer vision), METADATA, TRANSFORMER models

Dual-Branch Spatial–Spectral Transformer with Similarity Propagation for Hyperspectral Image Classification.

Autoren: Wen, Teng Wang, Heng Wang, Liguo

Quelle: Remote Sensing; Jul2025, Vol. 17 Issue 14, p2386, 30p

Schlagwörter: TRANSFORMER models, MULTILAYER perceptrons, DATA reduction, REMOTE-sensing images, SIMILARITY transformations

SMamba-KAN: an advanced temporal-nonlinear model for precise water level prediction.

Autoren: Yan, Xiangrui Zhao, Huijuan Zhou, Ruyan

Quelle: Frontiers in Water; 2025, p1-17, 17p

Schlagwörter: HYDROLOGICAL forecasting, PREDICTION models, TIME-varying systems, WATERSHEDS, MULTILAYER perceptrons, HYDROLOGICAL databases, TRANSFORMER models

Geografische Kategorien: YANGTZE River (China), DATONG (Shanxi Sheng, China)

Enhancing multi-class lung disease classification in chest x-ray images: A hybrid manta-ray foraging volcano eruption algorithm boosted multilayer perceptron neural network approach.

Autoren: Thavasimuthu, Rajendran Hanumanthakari, Sudheer Sekar, Sridhar et al.

Quelle: Network: Computation in Neural Systems; Aug2025, Vol. 36 Issue 3, p987-1018, 32p

Assessment of Landslide Susceptibility Based on the Two-Layer Stacking Model—A Case Study of Jiacha County, China.

Autoren: Wang, Zhihan Wen, Tao Chen, Ningsheng et al.

Quelle: Remote Sensing; Apr2025, Vol. 17 Issue 7, p1177, 24p

Schlagwörter: ENSEMBLE learning, LANDSLIDE hazard analysis, EMERGENCY management, STACKING machines, SUPPORT vector machines, LANDSLIDES

Predicting Liquid Natural Gas Consumption via the Multilayer Perceptron Algorithm Using Bayesian Hyperparameter Autotuning.

Autoren: Lee, Hyungah Cho, Woojin Park, Jong-hyeok et al.

Quelle: Energies (19961073); May2024, Vol. 17 Issue 10, p2290, 16p

Schlagwörter: NATURAL gas consumption, LIQUEFIED natural gas, NATURAL gas, GREENHOUSE gases, ENERGY consumption, FOOD processing plants, ALGORITHMS

Cycle based state of health estimation of lithium ion cells using deep learning architectures.

Autoren: Bairwa, Bansilal Pareek, Kapil Jadoun, Vinay Kumar

Quelle: Scientific Reports; 10/23/2025, Vol. 15 Issue 1, p1-22, 22p

Schlagwörter: LITHIUM-ion batteries, DEEP learning, BATTERY management systems, MULTILAYER perceptrons, LONG short-term memory, RECURRENT neural networks

DGGCCM: a hybrid neural model for legal event detection.

Autoren: Gong, Shutao Luo, Xudong

Quelle: Artificial Intelligence & Law; Dec2025, Vol. 33 Issue 4, p1109-1149, 41p

Schlagwörter: ARTIFICIAL neural networks, MULTILAYER perceptrons, GRAPH neural networks, LANGUAGE models, MACHINE learning

Machine learning-based defect prediction model using multilayer perceptron algorithm for escalating the reliability of the software.

Autoren: Juneja, Sapna Nauman, Ali Uppal, Mudita et al.

Quelle: Journal of Supercomputing; May2024, Vol. 80 Issue 7, p10122-10147, 26p

Schlagwörter: SOFTWARE reliability, SOFTWARE engineering, COMPUTER software quality control, PREDICTION models, COMPUTER software testing, SYSTEM failures

Real-time soil fertility analysis, crop prediction, and insights using machine learning and deep learning algorithms.

Autoren: Gunasekaran, Kanimozhi A., Karmel Sreevardhan, Pemmareddy

Quelle: Frontiers in Soil Science; 2025, p1-27, 27p

Schlagwörter: SOIL fertility, MACHINE learning, SUSTAINABLE agriculture, DEEP learning, PREDICTION models, REAL-time computing, AGRICULTURAL statistics, AGRICULTURAL forecasts