Antioptimisation of Trusses Using Two-Level Population-Based Incremental Learning by Phinit Tontragunrat, Sujin Bureerat

“…There have been several ways to deal with such optimisation problems, and one of the approaches is an antioptimisation process. …”
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Distribution network planning considering active response of EVs and DTR of cables and transformers by Chen Pan, Weijiang Chen, Chengke Zhou, Wenjun Zhou

“…In this paper, we propose a model considering the active response of EVs, and a bi‐level DNP model incorporating the DTR of cables and transformers, in the upper level, the Prim algorithm is embedded into the particle swarm optimisation (PSO) algorithm to obtain an initial grid topology; in the lower level, types of cables and transformers as well as the installation of DTR equipment are determined, second‐order cone (SOC) relaxation and linearisation of the variables product are then carried out to meet the non‐linear constraints of cables and transformers, and the upper and lower models are solved in an iterative manner. …”
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A high-entropy image encryption scheme using optimized chaotic maps with Josephus permutation strategy by Nawal El Ghouate, Mohamed Amine Tahiri, Ahmed Bencherqui, Hanaa Mansouri, Ahmed El Maloufy, Hicham Karmouni, Mhamed Sayyouri, Sameh Askar, Mohamed Abouhawwash

“…This algorithm uses Kepler Chaotic Optimisation Algorithm (CKOA) to select the most suitable chaotic maps, guaranteeing optimal diffusion and complex pixel confusion. …”
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Sustainable THz SWIPT via RIS-Enabled Sensing and Adaptive Power Focusing: Toward Green 6G IoT by Sunday Enahoro, Sunday Cookey Ekpo, Mfonobong Uko, Fanuel Elias, Rahul Unnikrishnan, Stephen Alabi, Nurudeen Kolawole Olasunkanmi

“…A weighted MMSE inner loop maximizes the data rate, while an outer alternating optimisation applies semidefinite relaxation to enforce passive-element constraints and SAR compliance. …”
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On optimum multi‐input multi‐output radar signal design: Ambiguity function, manifold structure and duration‐bandwidth by Yuqing Liu, Jia Xu, Kon Max Wong, Timothy N. Davidson

“…Comparing the designs using ED and RD, we find that the convergence of the algorithm can be significantly faster when optimising over the manifold (RD) than when optimising over the whole space (ED). …”
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Flexibility in load demand and PHEV parameters for clean and economic microgrid operation by Bishwajit Dey, Srikant Misra, Arnab Pal

“…This paper offers a novel one-to-one-based optimisation algorithm for minimising the generating cost of an MG system while considering various PHEV operational factors and DSM tactics. …”
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Prioritising explainable AI-driven recommendations with knowledge graphs and reinforcement learning by Neeraj Tiwary, Shahrul Azman Mohd Noah, Fariza Fauzi

“…To address this gap, we propose the Explainable Artificial Intelligence-driven Recommender System (XAIRec), which incorporates explainability mechanisms into knowledge graphs (KGs) and leverages knowledge graph embeddings (KGEs) alongside reinforcement learning (RL) to enhance both transparency and interpretability. By applying optimisation techniques that consider rewards, probabilities, information values, and affinity scores while minimising traversal hops within KG paths, XAIRec learns user preferences from historical data, determines optimal reasoning paths, and enhances recommendation quality by prioritising products with higher relevance. …”
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Abilities and limitations in counteracting urban heat islands by Michał Musiał, Anna Pomykała, Lech Lichołai

“…The ability to process vast amounts of data allows for more effective use of energy and water resources in buildings while continuously improving the algorithm. The literature review involved a comparison of current methods used to counteract urban heat islands, as well as existing and potential applications of artificial intelligence algorithms described in the Scopus and Web of Science databases. …”
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Investigating the dynamics and uncertainties in portfolio optimization using the Fourier-Millen transform. by Muhammad Hilal Alkhudaydi, Aiedh Mrisi Alharthi

“…These are then compared with other algorithms, such as vector autoregression, in portfolio optimisation tests. …”
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Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

“…This study proposes a novel optimisation approach utilising deep learning to tackle these challenges. …”
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Location allocation approach based on influence of points of dispensing by Nusaybah Alghanmi, Reem Alotaibi, Sultanah Alshammari, Arif Mahmood

“…A considerable amount of research has been conducted to determine the number and location of new PODs while keeping existing ones operational. A query-based approach needs data on the number of new PODs in advance, and an optimisation-based approach requires the specification of distance and percentage gap as constraints or objective to ensure the required population coverage is achieved. …”
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Research on SeaTreasure Target Detection Technology Based on Improved YOLOv7-Tiny by Xiang Shi, Yunli Zhao, Jinrong Guo, Yan Liu, Yongqi Zhang

“…Experimental results demonstrate that our optimized algorithm achieves a mAP0.5 of 79.5%, representing a 2.0 percentage point improvement over the baseline YOLOv7-tiny model (77.5%) while maintaining computational efficiency at 45.2 GFLOPs. …”
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THE ROLE OF ARTIFICIAL INTELLIGENCE IN PERSONALISED MEDICINE: ADVANCEMENTS, CHALLENGES, AND FUTURE PERSPECTIVES by Ioana-Marcela PĂCURARU, Ciprian-Sorin CHIRVASE, Ştefan-Ioan TIRITEU

“…It explores AI’s role in diagnostics, personalised treatment strategies, and the optimisation of medical workflows, while critically examining ethical and legal challenges. …”
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Adaptive and dynamic smart traffic light system for efficient management of regular and emergency vehicles at city intersection by Rafik Zerroug, Zibouda Aliouat, Makhlouf Aliouat, Adel Alti

“…The proposed system also uses the Weight Chicken Swarm Optimisation algorithm for decision‐making to reduce congestion and average vehicle waiting time significantly. …”
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Multi-criteria placement and sizing of utility-scale grid forming converters by Francisco S. Fernandes, João Peças Lopes, Carlos L. Moreira

“…Such methodology, which includes a collection of techniques to reduce the problem dimensionality, formulates the placement problem as a non-linear multi-criteria decision support problem and uses a solution-seeking algorithm based on Bayesian Optimisation to determine the solution. …”
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Using 'sentinel' plants to improve early detection of invasive plant pathogens. by Francesca A Lovell-Read, Stephen Parnell, Nik J Cunniffe, Robin N Thompson

“…Using Xylella fastidiosa infection in Olea europaea (European olive) as a current high profile case study, for which Catharanthus roseus (Madagascan periwinkle) is a candidate sentinel host, we apply a Bayesian optimisation algorithm to determine the optimal number of sentinel hosts to introduce for a given sampling effort, as well as the optimal division of limited surveillance resources between crop and sentinel plants. …”
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Advancing Sika deer detection and distance estimation through comprehensive camera calibration and distortion analysis by Sandhya Sharma, Stefan Baar, Bishnu P. Gautam, Shinya Watanabe, Satoshi Kondo, Kazuhiko Sato

“…The Solar Powered 4K-trail and HC-801A-Pro exhibited barrel distortion, while the HC-801A exhibited pincushion distortion. …”
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A machine learning approach to population pharmacokinetic modelling automation by Sam Richardson, Itziar Irurzun Arana, Andrzej Nowojewski, Diansong Zhou, Jacob Leander, Weifeng Tang, Richard Dearden, Megan Gibbs

“…This study demonstrates an automated, out-of-the-box approach for popPK model development, leveraging optimisation algorithms implemented using pyDarwin to efficiently handle a diverse range of extravascular drugs. …”
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The Analysis of the Possibility to Conduct Orbital Manoeuvres of Nanosatellites in the Context of the Maximisation of a Specific Operational Task by Magdalena Lewinska, Michal Kedzierski

“…It is suggested that future research should develop towards more advanced optimisation techniques, such as artificial intelligence algorithms that may additionally improve the precision and efficiency of planning orbital trajectories.…”
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Hybridize Machine Learning Methods and Optimization Techniques to Analyze and Repair Welding Defects via Digital Twin of Jidoka Simulator by Ahmed M. Abed, Tamer S. Gaafar

“…Hybridising the Random-Forest algorithm with Dingo optimisation and called Regulated Random Forest (RRF) to precisely identify defect clusters and then predict the welding defect growth rate (<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {{R}_{s}}$ </tex-math></inline-formula>) using the Cat-boost optimiser, which is enhanced by a beetle search mechanism called CatBAS. …”
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