A Contrastive-Augmented Memory Network for Anti-UAV Tracking in TIR Videos by Ziming Wang, Yuxin Hu, Jianwei Yang, Guangyao Zhou, Fangjian Liu, Yuhan Liu

“…Comprehensive experiments have been conducted on the Anti-UAV410 dataset, where the proposed CAMTracker achieves the best performance compared to advanced tracking algorithms, with significant advantages on all the evaluation metrics, including at least 2.40%, 4.12%, 5.43% and 5.48% on precision, success rate, success AUC and state accuracy, respectively.…”
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Optimized breast cancer diagnosis using self-adaptive quantum metaheuristic feature selection by Alok Kumar Shukla, Shubhra Dwivedi, Deepak Singh, Sunil Kumar Singh, Diwakar Tripathi, Ram Kishan Dewangan

“…Comparative results based on optimal computing time and performance are also offered to empirically analyze the traditional algorithms. …”
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Comparative Characteristics of the Results of Evacuation to Healthcare Facilities and Treatment Outcomes of Children Who Applied for First Aid With Acute Abdominal Pains. The Case... by Ekaterina А. Romanova, Leyla S. Namazova-Baranova, Elena Yu. Dyakonova, Aleksey Yu. Romanov, Kazbek S. Mezhidov, Zharadat I. Dohshukaeva

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A Quality Soft Sensing Method Designed for Complex Multi-process Manufacturing Procedures by Kaixiang PENG, Xin QIN, Jiahao WANG, Hui YANG

“…To further verify the effectiveness of the proposed multi-sensor process variable selection method, comparative tests are conducted using the four correlation-based feature selection algorithms (PCC, SCC, MI, and MIC) with the same number of selected features for each algorithm. …”
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House Market Prediction Using Machine Learning by Nicușor-Andrei ANDREI

“…This study compares tree-based machine learning algorithms for predicting Bucharest residential apartment prices. …”
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A bi-decision model for electric vehicle dispatch and battery swapping station charging schedule problem by Yong Su, Shishun Tian, Hao Wu, Xia Li

“…Knowing that two models are both Non-deterministic Polynomial-time hard (NP-hard) problems, two types of evolutionary algorithms are proposed. In the first model, an adaptive tabu search (ATS) algorithm is proposed by formatting the EVs’ ET, the number of batteries, and queuing EVs at BSSs. …”
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Identification and Evaluation of Profitable Technical Trading Rules in the Cryptocurrency Market: A Mixed Method Approach by Milad Abbasi, Somayeh Al-sadat Mousavi, Abbasali Jafari Nodoushan

“…Then, the parameters of the expert-based trading rules were optimized using two metaheuristic algorithms, namely grid search and particle swarm optimization. …”
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Optimizing Heart-Kidney Interaction for Cancer Detection Through Physiological Process Simulation as a Decision Support System by Najmeh Sadat Jaddi, Salwani Abdullah, Zalinda Othman, Yazrina Yahya, Mohd Zakree Ahmad Nazri, Say Leng Goh, Fatemeh Alvankarian, Jafar Alvankarian

“…The heart component enhances the KA’s local search capability, guiding the algorithm toward optimal solutions. …”
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Wasserstein Distributionally Robust Optimization for Chance Constrained Facility Location Under Uncertain Demand by Iman Seyedi, Antonio Candelieri, Enza Messina, Francesco Archetti

“…To overcome this limitation, the proposed approach integrates two methodologies, specifically a Genetic Algorithm to search for the optimal decision about facility opening, inventory, and allocation, and a constrained Jordan–Kinderlehrer–Otto (cJKO) scheme for dealing with robustness in the objective function and chance-constraint with respect to possible unknown fluctuations in demand. …”
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Comparing FIB-4, VCTE, pSWE, 2D-SWE, and MRE Thresholds and Diagnostic Accuracies for Detecting Hepatic Fibrosis in Patients with MASLD: A Systematic Review and Meta-Analysis by Mitchell Patrick Wilson, Ranjit Singh, Shyam Mehta, Mohammad Hassan Murad, Christopher Fung, Gavin Low

“…A modified two-tier algorithm aligning with existing Society of Radiologists in Ultrasound guidelines would improve risk stratification accuracies compared to existing guidelines by European and American liver societies.…”
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Thermodynamic optimization of a multi-generation system integrating gas turbine-helium reactor cycle with hydrogen production and desalination by Yang Wang, Yuliang Chen, Zhen Su

“…The Red Kite Optimization Algorithm (ROA), a novel metaheuristic inspired by the social behavior of red kites, is employed for both single- and multi-objective optimization. …”
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TDR-Model: Tomato Disease Recognition Based on Image Dehazing and Improved MobileNetV3 Model by Zhixiang Zhang, Tong Liu, Jinyu Gao, Meng Yang, Wenjun Luo, Fanqiang Lin

“…Employing the quad-tree spatial hierarchy search strategy, guided filtering, tolerance mechansim, and multi-scale color restoration (MSRCR) algorithm, an innovative improved version of DCP dehazing algorithm is realized. …”
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Using artificial intelligence methods for the optimal synthesis of reversible networks by Taras Kyryliuk, Mykhailo Palahuta, Vitaly Deibuk

“…The research synthesized optimal reversible circuits based on reversible gates using evolutionary algorithms and compare them with existing analogues. …”
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Chaotic-mapping and Gaussian perturbation-based multi-channel constant modulus blind equalization by HU Shuang, FENG Jiao, ZHANG Zhizhong, LI Peng, ZHOU Hua

“…In addition, by comparing different inertia weight schemes, it is further verified that the proposed algorithm achieves faster convergence speed and lower inter-symbol interference.…”
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Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…To address the multi-factor coupling, temporal dependency, and nonlinear complexity characteristics of concrete dam deformation, this paper proposed a hybrid prediction model integrating attention mechanisms, bidirectional long short-term memory (BiLSTM) networks, and sparrow search algorithm (SSA). The model comprehensively matched the multiple requirements of information weighting, temporal dependency modeling, and model optimization in concrete dam deformation prediction, forming a synergistic enhancement effect among methods.The attention mechanism operates on both feature and temporal dimensions to comprehensively enhance the model's focus on critical information. …”
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Improved Lyrebird optimization for multi microgrid sectionalizing and cost efficient scheduling of distributed generation by Karthik Nagarajan, Arul Rajagopalan, Mohit Bajaj, Valliappan Raju, Vojtech Blazek, Lukas Prokop

“…Additionally, a chaotic sine map is integrated to enhance global search capability, ensuring better diversity and superior optimization performance compared to traditional algorithms. …”
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Dual Strategy Based Improved Swarm Intelligence and Stacked LSTM With Residual Connection for Land Use Land Cover Classification by Vinaykumar Vajjanakurike Nagaraju, Ananda Babu Jayachandra, Andrzej Stateczny, Swathi Holalu Yogesh, Raviprakash Madenur Lingaraju, Balaji Prabhu Baluvaneralu Veeranna

“…This article proposes a dual strategy-based bald eagle search (DSBES) algorithm and stacked long short-term memory (LSTM) with residual connection for LULC classification. …”
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Vessel Traffic Flow Prediction in Port Waterways Based on POA-CNN-BiGRU Model by Yumiao Chang, Jianwen Ma, Long Sun, Zeqiu Ma, Yue Zhou

“…The results indicate that the POA algorithm has better global search capability and faster convergence than other optimization algorithms in the experiment. …”
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Noise Reduction of Steam Trap Based on SSA-VMD Improved Wavelet Threshold Function by Shuxun Li, Qian Zhao, Jinwei Liu, Xuedong Zhang, Jianjun Hou

“…The sparrow search algorithm, using minimum envelope entropy as the fitness function, optimizes the decomposition level <i>K</i> and the penalty factor α of the variational modal decomposition algorithm. …”
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Predictive Models for Educational Purposes: A Systematic Review by Ahlam Almalawi, Ben Soh, Alice Li, Halima Samra

“…This systematic literature review evaluates predictive models in education, focusing on their role in forecasting student performance, identifying at-risk students, and personalising learning experiences. The review compares the effectiveness of machine learning (ML) algorithms such as Support Vector Machines (SVMs), Artificial Neural Networks (ANNs), and Decision Trees with traditional statistical models, assessing their ability to manage complex educational data and improve decision-making. …”
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