An efficient cost calculation method for disparity estimation of stereo matching considering shadow occlusion by Hongjun Sha, Wei Yuan, Xunping Wang, Xiuliu Yuan, Shunichi Koshimura

“…To verify the optimization ability and transferability of MCSP, the MCSP cost is integrated into three classical disparity estimation algorithms respectively. …”
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Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders. by Zuhair Alaas, Ghareeb Moustafa, Hany Mansour

“…The PO is a novel bio-inspired optimization algorithm that draws inspiration from pelicans' intelligence and behavior which incorporates unique methods for exploration and exploitation, improving its effectiveness in various optimization challenges. …”
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A Novel Tornado Detection Algorithm Based on XGBoost by Qiangyu Zeng, Guoxiu Zhang, Shangdan Huang, Wenwen Song, Jianxin He, Hao Wang, Yin Liu

“…In addition, the TDA-XGB algorithm combines artificial intelligence-assisted learning to optimize the traditional algorithm based on the tornado vortex signature (TVS) and tornado debris signature (TDS), further improving the detection effect. …”
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An Efficient and Cost-Effective Vehicle Detection and Tracking System for Collision Avoidance in Foggy Weather by Naeem Raza, Muhammad Asif Habib, H. M. Sajid Imran, Abdul Qayum, Sajida Perveen, Sohail Jabbar, Shahzad Sarwar, Mudassar Ahmad

“…The proposed ECE-VDT system encompasses an optimized SimYOLO-V5s algorithm and its five variants for vehicle detection, while the optimized deep-SORT algorithm is proposed for vehicle tracking. …”
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Forecast-based resource reconfiguration algorithm for network virtualization by ZHANG Shun-li, QIU Xue-song, PAN Ya-lian, MENG Luo-ming

“…In order to solve imbalance issues of used resources of substrate network,which are brought by virtual net-work joining and leaving dynamically,forecast-based resource reconfiguration algorithm（FRRA） for network virtualiza-tion environment was proposed.Algorithm FRRA took full advantage of known information to calculate interval of re-configuration and used this interval to replace the periodic time span in previous algorithms.In order to make reconfigu-ration time global optimal,it took two measures:resources were divided into critcal resources and general resources,and different algorithms were used to key resources and common resources respectively;according to the probability that re-source migration was failure,the limit number of reconfiguration requests was deduced.FRRA algorithm with VNA-II algorithm and PMPA algorithm in the experiments was compared.The results show that algorithm FRRA reduces recon-figuration cost 69% than that of VNA-II and 42% than that of PMPA.Algorithm FRRA improves VN request reception rate 29% than that of VNA-II and 52% than that of PMPA.…”
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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…Thus, this study has developed a novel feature-based enhanced boosting algorithm (F-EBA). The proposed model covers two pipelines, the feature engineering pipeline which improves the quality of features by picking up the most relevant features while the classification pipeline uses an ensemble approach designed to boost/elevate the model’s performances. …”
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Democratization of Crop Irrigation: A Socio-Technical Optimization Approach Using Particle Swarm Optimization by Hasna Elalaoui Elabdallaoui, Youssef Mourdi, Abdelaziz ElFazziki, Mohamed Sadgal

“…It examines how this equitable irrigation approach can contribute to the social economy by improving irrigation efficiency and reducing costs for farmers. …”
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Optimizing Euclidean Distance Computation by Rustam Mussabayev

“…The Euclidean distance, being a computational bottleneck in large-scale optimization problems, requires efficient computation techniques to improve the performance of various distance-dependent algorithms. …”
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Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques by Poonam Saroha, Gopal Singh, Umesh Kumar Lilhore, Sarita Simaiya, Monish Khan, Roobaea Alroobaea, Majed Alsafyani, Hamed Alsufyani

“…These dynamics are difficult for traditional systems to handle, but new developments in reinforcement learning and optimization may be able to help. The paper introduces a novel Demand Response (DR) method that integrates a Self-Adaptive Puma Optimizer Algorithm (SAPOA) with a Multi-Objective Deep Q-Network (MO-DQN), improving smart home energy consumption, cost, and user preferences management. …”
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GaLAM: Two-Stage Outlier Detection Algorithm by Xiaojun Lu, Zhe Yan, Ziyun Fan

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Algorithm for Selection Equipment to Reduce the Technogenic Effect on the Environment by Kozii I.S., Plyatsuk L.D., Koval V.V.

“…The proposed algorithm, in contrast to the approaches used in practice, was characterized by the work flexibility due to the possibility of supplementing and improving the databases of pollutants and equipment.…”
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Hybrid Raft-PoW Blockchain Consensus Algorithm by Mehtap Kose Ulukok, Irfan Sariyildiz, Vesile Evrim

“…The Raft consensus algorithm’s voting mechanism performs well in reliable and well-planned networks with optimized timeouts. …”
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Algorithms for Integrated Object Detection in Wireless Sensor Networks by V. I. Parfenov, T. T. Bui

“…Wireless sensor networks can be used to solve various economic problems, including detection of objects (phenomena) of interest. Most of the well-known information processing algorithms in such networks are built according to a radial architecture. …”
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Using machine learning algorithms to predict colorectal polyps by Xingjian Xiao, Shiyou Liu, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Xianglong Xu

“…Background: Colorectal cancer (CRC) is the third most common cancer worldwide, and colorectal polyps (CRP) represent a necessary pathway to the development of CRC. …”
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Network- and Demand-Driven Initialization Strategy for Enhanced Heuristic in Uncapacitated Facility Location Problem by Jayson Lin, Shuo Yang, Kai Huang, Kun Wang, Sunghoon Jang

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Revolutionizing RPAS logistics and reducing CO2 emissions with advanced RPAS technology for delivery systems by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte, Richard C. Millar, Robert Walter Meyer

“…The use of the NSGA-II meta-heuristic method for validation enhances the credibility and practicality of the model. The optimization model’s performance over 250 generations shows rapid initial improvements in cost, time, risk, and battery usage, followed by stabilization, indicating efficient convergence and effective evolutionary computation. …”
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Navigating Intelligence: A Survey of Google OR‐Tools and Machine Learning for Global Path Planning in Autonomous Vehicles by Alexandre Benoit, Pedram Asef

“…This problem is central to enhancing ROMIE's operational efficiency and competitiveness against human labor by optimizing cost and time. The primary aim of this research is to advance GPP by developing, evaluating, and improving a cost‐efficient software and web application. …”
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Framework for truck–RPAS hybrid models in last-mile delivery by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte

“…High-quality Pareto-optimal solutions are produced by the non-dominated sorting genetic algorithm II, which methodically manages trade-offs between the conflicting goals. …”
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Decentralized Voltage and Var Control of Active Distribution Network Based on Parameter-Sharing Deep Reinforcement Learning by Binqiao Zhang, Changlin He

“…By allowing agents to share parts of their neural network, the proposed Parameter Sharing - twin-delay deep deterministic policy gradient algorithm improves the stability and efficiency of voltage regulation. …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…The algorithm divides the population into two parts, using the non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization algorithm (MOPSO) for solving, with improvements to enhance the algorithm’s performance. …”
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