Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

“…[Results] The study introduced four key innovations to the original Mantis Search Algorithm (MSA): (1) combining Logistic-Tent chaotic mapping for population initialization, ensuring uniform and random distribution of initial solutions to enhance global search capability and convergence speed; (2) nonlinear acceleration factor, refining MSA’s core update formula to transition from global exploration to local exploitation, mitigating local optima entrapment; (3) elite-guided adaptive update strategy, addressing the excessive randomness in the position update strategy when Mantis attacks fail, improving late-stage search efficiency while preserving some randomness; (4) opposition-based learning, generating individuals opposite to the current individual to enhance global optimization. …”
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METAHEURISTIC-DRIVEN MULTI OBJECTIVE FIR FILTER DESIGN FOR ECG DENOISING by Mehmet Fatih Karakaş, Fatma Latifoğlu

“…The research employs advanced metaheuristic algorithms, including Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Genetic Algorithm (GA), Black Widow Optimization (BWO), Chaos Game Optimization (CGO), Harmony Search (HS), Squirrel Search Algorithm (SSA), and Atomic Orbital Search (AOS) to optimize multiple filter design parameters jointly. …”
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A Two-Stage Robust Optimization Strategy for Long-Term Energy Storage and Cascaded Utilization of Cold and Heat Energy in Peer-to-Peer Electricity Energy Trading by Yun Chen, Yunhao Zhao, Xinghao Zhang, Ying Wang, Rongyao Mi, Junxiao Song, Zhiguo Hao, Chuanbo Xu

“…The strategy includes a UIES model with a photovoltaic (PV)–green roof, hydrogen storage, and cascading cold/heat energy subsystems. The first stage optimizes energy trading volume to maximize social welfare, while the second stage maximizes operational profit, considering uncertainties in PV generation and power prices. …”
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Optimal Sizing, Techno-Economic Feasibility and Reliability Analysis of Hybrid Renewable Energy System: A Systematic Review of Energy Storage Systems’ Integration by Akhlaque Ahmad Khan, Ahmad Faiz Minai, Rakesh Kumar Godi, Vijay Shankar Sharma, Hasmat Malik, Asyraf Afthanorhan

“…Findings emphasize the need for further study of optimization methods, meta-heuristic algorithm strategies, system components, design constraints, and desired techniques.…”
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Evaluating Customer Segmentation Techniques in the Retail Sector by Nur Diyabi, Duygu Çakır, Ömer Melih Gül, Tevfik Aytekin, Seifedine Kadry

“…DBSCAN showed strengths in identifying non-spherical clusters, while GMM and SOM provided more granular segmentation. …”
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Fault diagnosis of MMC-MTDC based on traveling wave characteristics and KOA-CNN-BiGRU-AM by Bo YU, Xuejun GAO, Can WANG, Ruiling LI, Yanbin XU, Mengjie RONG

“…On this basis, the Kepler optimization algorithm （KOA） and attention mechanism （AM） are employed to enhance the CNN-BiGRU network to realize the fault diagnosis of the MMC-MTDC. …”
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Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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Three-stage hybrid scheduling method based on link adjustment and arc replacement for large-scale satellite ground station resource scheduling considering idleness rate by Shunyi Cao, Xiaolu Liu, Lei He

“…Then, a Local-tabu Optimization Operator Based on Arc Replacement (LTOO-AR) enhances the idleness rate by replacing task arcs while introducing a local-tabu strategy to prevent the algorithm from becoming trapped in local optima. …”
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Construction and Application Analysis of an Intelligent Distribution Network Identification System Based on Deep Neural Networks by Yu Ma

“…In addition, the Cross-Validation Grid Search Algorithm (GSA) was used to optimize the hyperparameters to ensure that the model can achieve the optimal performance on different data sets. …”
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Energy-Efficient and Fault-Tolerant Control of a Six-Axis Robot Based on AI Models by Patryk Nowak, Zoran Pandilov

“…Obstacles are present in the robot’s workspace. The goal of the algorithm is to control the robot in such a way that energy consumption is minimized while also avoiding obstacles and ensuring fault tolerance in the event of axis failures. …”
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Calibrating multiplex serology for Helicobacter pylori by Emmanuelle A. Dankwa, Martyn Plummer, Daniel Chapman, Rima Jeske, Julia Butt, Michael Hill, Tim Waterboer, Iona Y. Millwood, Ling Yang, Christiana Kartsonaki

“…We discuss these challenges and propose a novel solution to optimize the translation of the continuous measurements from multiplex serology into probabilities of H. pylori infection, using classification algorithms (Bayesian additive regressive trees (BART), multidimensional monotone BART, logistic regression, random forest and elastic net). …”
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Spatial Simulation and Optimization of Cropping Structure Under Climate and Land Use Change Conditions Considering Synergistic Economic Benefits and Carbon Reduction in Crop Growth... by Mo Li, Haiyan Li, Zhaoqiang Zhou, Yingshan Chen, Yijia Wang, Tianxiao Li, Qiang Fu

“…This approach is based on climate change conditions and it accurately simulates future land use changes and crop growth processes, establishes a carbon emission intensity optimization model, and generates a spatial planting structure optimization and regulation scheme based on intelligent optimization algorithms under changing scenarios. …”
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Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings by Rayan Khalil, Guilherme Vieira Hollweg, Akhtar Hussain, Wencong Su, Van-Hai Bui

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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Optimizing AI Transformer Models for <italic>CO</italic>&#x2082; Emission Prediction in Self-Driving Vehicles With Mobile/Multi-Access Edge Computing Support by Javier Saez-Perez, Pablo Benlloch-Caballero, David Tena-Gago, Jose Garcia-Rodriguez, Jose Maria Alcaraz Calero, Qi Wang

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The Fine Feature Extraction and Attention Re-Embedding Model Based on the Swin Transformer for Pavement Damage Classification by Shizheng Zhang, Kunpeng Wang, Zhihao Liu, Min Huang, Sheng Huang

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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…We have evaluated the accuracy of our proposed technique against state-of-the-art biomimetic computing models such as GA, PSO, GWO, DE, and ACO. While ACO achieved up to 89.45% accuracy, our Bayesian Optimization with LSTM outperformed all others, reaching a peak accuracy of 95.55%, demonstrating its effectiveness in enhancing spoken language identification. …”
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The diagnostic accuracy of the ESC 0/1-hour algorithm in non-ST-segment elevation myocardial infarction in a crowded emergency department: a real-world experience from a single-cen... by Emre Kudu, Ahmet Enes Kucukardali, Mustafa Altun, Ümit Öztürk, Erhan Altunbaş, Sinan Karacabey, Erkman Sanri, Arzu Denizbasi

“…The European Society of Cardiology (ESC) 0/1-hour algorithm, utilizing high-sensitivity cardiac troponin T (hs-cTnT) levels, has demonstrated high diagnostic performance internationally. …”
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Embedded Rough-Neck Helmholtz Resonator Low-Frequency Acoustic Attenuator by Xianming Sun, Tao Yu, Lipeng Wang, Yunshu Lu, Changzheng Chen

“…Moreover, by coupling the BP network with the Golden Jackal Optimization (GJO) algorithm, a BP-GJO optimization model is developed to refine the structural parameters. …”
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Distributed Robust Low-Carbon Economic Dispatch of Power Systems Considering Extreme Scenarios by HU Heng, QIN Jianru, LI Haibo, LIU Jiefeng

“…[Methods] To address this， this paper first constructs RE generation scenarios using Latin hypercube sampling （LHS） and modified k-means clustering， verifying their reserve feasibility， while transforming reserve-infeasible scenarios into extreme scenario sets. …”
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