Search Results - multi-objective genetic algorithm explainer

Model-agnostic local explanation: Multi-objective genetic algorithm explainer

Authors: Hossein Nematzadeh José García-Nieto Sandro Hurtado et al.

Source: RIUMA. Repositorio Institucional de la Universidad de Málaga
Universidad de Málaga

Subject Terms: Residual network 50 layers, Local Interpretable Model-agnostic Explanations, Citrus diseases, Non-dominated Sorting Genetic Algorithm II, Programación genética (Informática), Melanoma detection, Multi-objective genetic algorithm explainer

Access URL: https://hdl.handle.net/10630/35359
https://doi.org/10.1016/j.engappai.2024.109628
https://hdl.handle.net/10630/35359

Genetic Algorithm Approach to a Concurrent Real-Time Optimization Problem in the Embedded System Design Process.

Authors: Górski, Adam M. Ogorzałek, Maciej

Source: Foundations of Computing & Decision Sciences; Sep2025, Vol. 50 Issue 3, p373-382, 10p

Subject Terms: GENETIC algorithms, EMBEDDED computer systems, MATHEMATICAL optimization, PARALLEL processing, EVOLUTIONARY algorithms, PROCESS optimization

Reduction of Insolvency Risk and Total Costs in Banking Sector using Partners Selection Approach with Genetic Algorithm and Multilayer Perceptron Neural Network.

Authors: Azarbad, M. Shojaie, A. A. Abdi, F. et al.

Source: International Journal of Engineering Transactions B: Applications; Aug2024, Vol. 37 Issue 8, p1667-1690, 24p

Subject Terms: BANKING industry, OPTIMIZATION algorithms, MULTILAYER perceptrons, ECONOMIC development, BANKRUPTCY, COST control, GENETIC algorithms, INTELLIGENT networks, METAHEURISTIC algorithms

GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation.

Authors: Mahmoud, Eman Alkhalaf, Salem Senjyu, Tomonobu et al.

Source: Scientific Reports; 7/26/2025, Vol. 15 Issue 1, p1-24, 24p

Subject Terms: IMAGE segmentation, THRESHOLDING algorithms, LEVY processes, MATHEMATICAL programming, SIGNAL-to-noise ratio, GENETIC algorithms, OPTIMIZATION algorithms, MATHEMATICAL optimization

MULTI-CRITERIA OPTIMIZATION OF DIGITAL MARKETING FOR ENTERPRISES IN THE AGRO-INDUSTRIAL COMPLEX BASED ON NSGA-III ALGORITHM AND MACHINE LEARNING.

Alternate Title: БАГАТОКРИТЕРІАЛЬНА ОПТИМІЗАЦІЯ ЦИФРОВОГО МАРКЕТИНГУ ДЛЯ ПІДПРИЄМСТВ АГРОПРОМИСЛОВОГО КОМПЛЕКСУ НА ОСНОВІ АЛГОРИТМУ NSGA-III ТА МАШИННОГО НАВЧАННЯ. (Ukrainian)

Authors: Kryvoruchko, Olena Abildaeva, Zhansaya Lakhno, Valerii et al.

Source: Eastern-European Journal of Enterprise Technologies; 3/25/2025, Vol. 135 Issue 4, p6-17, 12p

Subject Terms: MULTI-objective optimization, AGRICULTURAL marketing, SOFTWARE libraries (Computer programming), MACHINE learning, INTERNET marketing

Optimized deep learning framework for pomegranate disease detection using nature-inspired algorithms.

Authors: Sandhi, Anil Kumar, Rajeev Bhardwaj, Reeta et al.

Source: Plant Methods; 10/3/2025, Vol. 21 Issue 1, p1-36, 36p

Subject Terms: DEEP learning, POMEGRANATE, IMAGE processing, PRECISION farming, BIOLOGICALLY inspired computing, OPTIMIZATION algorithms, PARTICLE swarm optimization

Research on Multi-Objective Parameter Matching and Stepwise Energy Management Strategies for Hybrid Energy Storage Systems.

Authors: Xu, Wenna Huang, Hao Wang, Chun et al.

Source: Energies (19961073); Mar2025, Vol. 18 Issue 6, p1354, 22p

Subject Terms: HYBRID power systems, MULTI-objective optimization, ENERGY storage, PARTICLE swarm optimization, ENERGY conservation

Multi-scale level set image segmentation model based on genetic selection.

Authors: Chen, Weiyueheng Lu, Yibin Wu, Dean et al.

Source: Signal, Image & Video Processing; Jun2025, Vol. 19 Issue 6, p1-19, 19p

Machine learning-aided catalyst screening and multi-objective optimization for the indirect CO2 hydrogenation to methanol and ethylene glycol process.

Authors: Yang, Qingchun Fan, Yingjie Zhou, Jianlong et al.

Source: Green Chemistry; 9/21/2023, Vol. 25 Issue 18, p7216-7233, 18p

Subject Terms: MACHINE learning, ETHYLENE glycol, HYDROGENATION, PEARSON correlation (Statistics), METHANOL, CATALYSTS, CARBONATES

Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization.

Authors: Mehdiyev, Nijat Majlatow, Maxim Fettke, Peter

Source: Cognitive Computation; Sep2024, Vol. 16 Issue 5, p2674-2700, 27p

Forecasting Turning Points of Carbon Emissions in Beijing Based on Interpretable Machine Learning.

Authors: Yao, Tianen Wang, Yaqi Li, Xinhao et al.

Source: Atmosphere; Aug2023, Vol. 14 Issue 8, p1288, 10p

Subject Terms: CARBON emissions, INDUSTRIAL energy consumption, CLIMATE change, CARBON offsetting, KUZNETS curve, MACHINE learning

Geographic Terms: BEIJING (China), CHINA

ParetoLens: A Visual Analytics Framework for Exploring Solution Sets of Multi-Objective Evolutionary Algorithms [Application Notes].

Authors: Ma, Yuxin Zhang, Zherui Cheng, Ran et al.

Source: IEEE Computational Intelligence Magazine; Feb2025, Vol. 20 Issue 1, p78-94, 17p

Toward Transparent Optimization: A Systematic Review of Explainable AI in Decision-Making Systems.

Authors: Danach, Kassem Aly, Wael Hosny Fouad Tarhini, Abbas et al.

Source: European Journal of Pure & Applied Mathematics; Oct2025, Vol. 18 Issue 4, p1-28, 28p

Heart disease prediction with a feature-sensitized interpretable framework for the Internet of Medical Things sensors.

Authors: Kailasanathan, Nallakaruppan Ezhilarasan, Gangadevi Selvarajan, Shitharth et al.

Source: Frontiers in Digital Health; 2025, p1-27, 27p

Subject Terms: HEART disease diagnosis, BOOSTING algorithms, RANDOM forest algorithms, ANGINA pectoris, PREDICTION models, SECONDARY analysis, RECEIVER operating characteristic curves, CLINICAL decision support systems, LOGISTIC regression analysis, DESCRIPTIVE statistics, HEART failure, SUPPORT vector machines, ELECTROCARDIOGRAPHY, HEART beat, CONCEPTUAL structures, DEEP learning, EARLY diagnosis, MACHINE learning, DECISION trees, DATA analysis software, INTERNET of things, SENSITIVITY & specificity (Statistics), BLOOD pressure measurement, CLOUD computing

Mathematical Modeling and Analysis of Credit Scoring Using the LIME Explainer: A Comprehensive Approach.

Authors: Aljadani, Abdussalam Alharthi, Bshair Farsi, Mohammed A. et al.

Source: Mathematics (2227-7390); Oct2023, Vol. 11 Issue 19, p4055, 28p

Subject Terms: CREDIT ratings, CREDIT analysis, PARTICLE swarm optimization, MATHEMATICAL analysis, DECISION trees, CLASSIFICATION algorithms, MATHEMATICAL models, MACHINE learning

Machine Learning for Multi-Target Drug Discovery: Challenges and Opportunities in Systems Pharmacology.

Authors: Bi, Xueyuan Wang, Yangyang Wang, Jihan et al.

Source: Pharmaceutics; Sep2025, Vol. 17 Issue 9, p1186, 30p

Subject Terms: MACHINE learning, PHARMACOLOGY, POLYPHARMACY, ETHICAL problems, ONCOLOGY, DEEP learning

Neuro-Bridge-X: A Neuro-Symbolic Vision Transformer with Meta-XAI for Interpretable Leukemia Diagnosis from Peripheral Blood Smears.

Authors: Jammal, Fares Dahab, Mohamed Bayahya, Areej Y.

Source: Diagnostics (2075-4418); Aug2025, Vol. 15 Issue 16, p2040, 32p

Subject Terms: CANCER diagnosis, MORPHOLOGY, ARTIFICIAL intelligence, LEUKOCYTES, CLINICAL decision support systems, CAUSAL artificial intelligence, TRANSFORMER models

Enhancing Credit Risk Prediction through an Ensemble of Explainable Model.

Authors: Sun, Xinyu Liu, Jiayu Zhang, Yan

Source: Journal of Systems Science & Systems Engineering; Oct2025, Vol. 34 Issue 5, p619-640, 22p

Designing an Optimization-Simulation Model for Credit Scoring and Loan Structuring Using a Memetic Algorithm: A Case Study of Corporate Banking Clients.

Authors: Khorrami, Amir Dehghan Nayeri, Mahmoud Rajabzadeh, Ali

Source: Industrial Management Journal (IMJ); 2025, Vol. 17 Issue 2, p27-57, 31p

Subject Terms: INTEREST rates, DEFAULT (Finance), ARTIFICIAL neural networks, CREDIT risk, CREDIT analysis, RECEIVER operating characteristic curves

Monthly Power Outage Maintenance Scheduling for Power Grids Based on Interpretable Reinforcement Learning.

Authors: Tang, Wei Mao, Xun Lv, Kai et al.

Source: Energies (19961073); Oct2025, Vol. 18 Issue 20, p5454, 18p

Subject Terms: REINFORCEMENT learning, MATHEMATICAL optimization, ELECTRIC power failures, SCHEDULING, ELECTRIC power system reliability, ELECTRIC power distribution grids