Results 71 to 80 of about 1,679 (197)

Deep reinforcement learning for multi‐restart metaheuristics: an environment design for a hybrid of unbiased exploratory search and covariance matrix adaptation evolution strategy

International Transactions in Operational Research, EarlyView.
Abstract Multi‐restart metaheuristics can be highly effective for complex optimization problems, yet their performance depends critically on how restarts and algorithmic parameters are selected. This paper introduces a reinforcement learning approach for managing restart‐level decisions and parameter configurations in the UES–CMA‐ES hybrid ...
Antonio Bolufé‐Röhler, Bowen Xu
wiley   +1 more source

Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods

EURASIP Journal on Wireless Communications and Networking, 2020
In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless ...
Hafiz Munsub Ali, Jiangchuan Liu, Waleed Ejaz   +2 more
doaj   +1 more source

Sampling rate selection for multi‐loop cascade control systems in an optimal manner

IET Control Theory & Applications, 2023
This article proposes an optimization‐based approach to selecting the sampling periods for classes of linear time‐invariant (LTI) regulators in a cascaded multi‐rate control structure, to account for practical implementation on numeric systems.
Mircea Şuşcă, Vlad Mihaly, Petru Dobra   +2 more
doaj   +1 more source

Machine Learning‐Based Loan Approval Automation: Enhancing Efficiency, Accuracy and Fairness in Credit Decision‐Making

Expert Systems, Volume 43, Issue 7, July 2026.
ABSTRACT Traditional loan approval processes are manual, time‐consuming and susceptible to human bias. This research develops a machine learning‐based system to automate loan eligibility assessment while enhancing efficiency, accuracy and fairness in credit decision‐making. We developed and compared multiple supervised ML models—including Random Forest,
Mani Ghahremani, Hellen Amimo Otieno, Mishanil Kazreen, Stavros Shiaeles   +3 more
wiley   +1 more source

Assessing forest fragmentation and biodiversity impacts in sub‐Saharan Africa: Methodological challenges and conservation strategies for small‐scale agricultural landscapes

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Tropical forests in sub‐Saharan Africa (SSA) harbor around one‐third of the world's species but are becoming more fragmented due to the expansion of human settlements and small‐scale agricultural (SCA) areas. This study systematically reviewed the approaches and methods used to analyze forest fragmentation and its impact on biodiversity in SSA,
Gillie Cheelo, Hastings Shamaoma, Charles Bwalya Chisanga, Jules Christian Zekeng, Stephen Syampungani   +4 more
wiley   +1 more source

An Efficient Optimization Algorithm for Resource-Constrained Steelmaking Scheduling Problems

IEEE Access, 2018
In this paper, we address the steelmaking scheduling problems with multiple constrained resources. The objective is to minimize the maximum completion time. We consider the continuous casting constraint and resource constraints simultaneously.
Junqing Li, Peiyong Duan, Hongyan Sang, Song Wang, Zhengmin Liu, Peng Duan   +5 more
doaj   +1 more source

Comparative Metaheuristic Optimization of PI Controllers for Electric Vehicle Speed Control

Engineering Reports, Volume 8, Issue 6, June 2026.
This paper presents the design, modeling, and simulation validation of an electric vehicle system, using speed variation as a reference to ensure optimal operation in terms of acceleration and deceleration. First, a conventional PI controller controls the vehicle's speed.
Samira Heroual, Belkacem Belabbas, Mohamed Metwally Mahmoud, Yasser Diab, Tayeb Allaoui, Vojtech Blazek, Daniel Eutyche Mbadjoun Wapet, Ali M. El‐Rifaie, Galal F. Abdelaal   +8 more
wiley   +1 more source

Artificial Flora (AF) Optimization Algorithm

Applied Sciences, 2018
Inspired by the process of migration and reproduction of flora, this paper proposes a novel artificial flora (AF) algorithm. This algorithm can be used to solve some complex, non-linear, discrete optimization problems.
Long Cheng, Xue-han Wu, Yan Wang
doaj   +1 more source

Optimization of discrete wavelet transform features using artificial bee colony algorithm for texture image classification

, 2019
Selection of appropriate image texture properties is one of the major issues in texture classification. This paper presents an optimization technique for automatic selection of multi-scale discrete wavelet transform features using artificial bee colony ...
Yussof, Wan Nural Jawahir Hj Wan, Hitam, Muhammad Suzuri, Muhammad Suzuri Hitam, Rozniza Ali, Albkosh, Fthi M., Hamid, Abdul Aziz K Abdul, Abdul Aziz K. Abdul Hamid, Wan Nural Jawahir Hj Wan Yussof, Fthi M. Albkosh, Ali, Rozniza   +9 more
core   +2 more sources

A review of participatory mapping in conservation science and practice

Conservation Science and Practice, Volume 8, Issue 6, June 2026.
There has been a recent increase and diversification in the use of participatory mapping in the field of conservation, however, methodological standards remain both disjointed and confounding. We conducted a comprehensive review of the conservation participatory mapping literature and synthesized geographical, temporal, and topical trends across a ...
Michael B. Kowalski, Christine E. Wilkinson, Christopher C. Wilmers, Natalia Ocampo‐Peñuela   +3 more
wiley   +1 more source