Portfolio Optimization with Translation of Representation for Transport Problems DOI Open Access

Małgorzata Zajęcka,

Mateusz Mastalerczyk, Siang Yew Chong

et al.

Journal of Artificial Intelligence and Soft Computing Research, Journal Year: 2024, Volume and Issue: 15(1), P. 57 - 75

Published: Dec. 8, 2024

Abstract The paper presents a hybridization of two ideas closely related to metaheuristic computing, namely Portfolio Optimization (researched by Xin Yao et al.) and Translation Representation for different metaheuristics Byrski al.). Thus, difficult problems (discrete optimization) are approached sequential run through number steps metaheuristics, providing the translation representation (since algorithms completely different). Therefore, close cooperation e.g. ACO, PSO, GA is possible. results refer unaltered show superiority constructed hybrid.

Language: Английский

6G digital twin and CPS system promote the development of rural architectural planning DOI
Zhai Binqing,

Yicong Yao,

Mohammad Khishe

et al.

Evolving Systems, Journal Year: 2025, Volume and Issue: 16(2)

Published: April 16, 2025

Language: Английский

Citations

0
Tracking Method for Alpine Skiing Based on Hybrid Deep Learning and Evolutionary Chimp Optimization Algorithm DOI Creative Commons
Xiaohua Wu,

Yongtao Shi,

Mohammad Khishe

et al.

Complexity, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

Tracking athletes in high‐speed outdoor sports like alpine skiing causes substantial difficulties because of ever‐changing movements, environmental variability, and the limitations traditional tracking technologies, such as intrusive sensors single‐view camera setups. This study proposes a hybrid approach for activities by combining YOLO‐v8 with an evolutionary version chimp optimization algorithm (CHOA‐EVOL) optimizing hyperparameters. The primary goal this research is to enhance CHOA optimally adjust hyperparameters YOLO‐v8, consequently addressing drawbacks technology. model integrates data from unmanned aerial vehicles (UAVs) terrestrial cameras better understand athletes’ rapid rotating motion. suggested extensively tested validated using advanced algorithms UAV123 dataset recently developed (ASD). results have shown that our proposed can achieve high precision robustness.

Language: Английский

Citations

0
A dual-adaptive stochastic reinforcement chimp optimization algorithm for fire detection and multidimensional problem solving DOI Creative Commons
Ziyang Zhang,

Lingye Tan,

Diego Martín

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 28, 2024

Language: Английский

Citations

2
A cognitive few-shot learning for medical diagnosis: A case study on cleft lip and palate and Parkinson’s disease DOI
Pei Yin, Junjie Song, Yassine Bouteraa

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 262, P. 125713 - 125713

Published: Nov. 4, 2024

Language: Английский

Citations

0
Objective-based survival individual enhancement in the chimp optimization algorithm for the profit prediction using financial accounting information system DOI Creative Commons

Guomeng Zhao,

Diego Martín, Mohammad Khishe

et al.

Engineering Science and Technology an International Journal, Journal Year: 2024, Volume and Issue: 60, P. 101897 - 101897

Published: Nov. 12, 2024

Language: Английский

Citations

0
Dynamic Lévy–Brownian marine predator algorithm for photovoltaic model parameters optimization DOI Creative Commons
Yassine Bouteraa, Mohammad Khishe

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 26, 2024

The dynamic and multimodal nature of photovoltaic (PV) systems makes it challenging to examine all solar characteristics. Consequently, this study recommends a recently developed optimization method called the marine predator algorithm (MPA) for developing reliable PV models. In traditional MPA, two main search processes are Lévy flight (LF) Brownian walk (BW), switch across them is unpredictable. This while transition between these mechanisms naturally continuous dynamic. To rectify limitation mentioned above, research paper presents an innovative, shift function that effectively modulates interplay exists BW LF procedures. By enhancing changeover pattern primary phases suggested substantially boosts performance MPA. Lévy-Brownian MPA (DLBMPA) also made be resilient in dealing with parameterization limitations Modeling approaches by using constraint handling technique. DLBMPA tested ten popular methods. Employing achieved average RMSE 9.7 × 10− 4 parameter estimation number multiple models, including SDM, DDM, TDM, where out algorithms experimented, was statistically significant (p < 0.05) better. terms averaged computation time, 13 ms still showed high accuracy different irradiance temperature levels. These improvements allow MBPA credited as having efficiency when estimating parameters since its speed convergence level surpass previous techniques used.

Language: Английский

Citations

0
Portfolio Optimization with Translation of Representation for Transport Problems DOI Open Access

Małgorzata Zajęcka,

Mateusz Mastalerczyk, Siang Yew Chong

et al.

Journal of Artificial Intelligence and Soft Computing Research, Journal Year: 2024, Volume and Issue: 15(1), P. 57 - 75

Published: Dec. 8, 2024

Abstract The paper presents a hybridization of two ideas closely related to metaheuristic computing, namely Portfolio Optimization (researched by Xin Yao et al.) and Translation Representation for different metaheuristics Byrski al.). Thus, difficult problems (discrete optimization) are approached sequential run through number steps metaheuristics, providing the translation representation (since algorithms completely different). Therefore, close cooperation e.g. ACO, PSO, GA is possible. results refer unaltered show superiority constructed hybrid.

Language: Английский

Citations

0