Minimum Error Integration Method for Quadrilateral Flat Plate Fitting in Steel Construction by Zhuoju Huang, Jiemin Ding

“…Our results demonstrate at most a 75.5% reduction in fitting errors for analytical curved plates with particularly significant improvements in biconvex curvature scenarios. …”
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A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY by Lev Raskin, Yurii Parfeniuk, Larysa Sukhomlyn, Mykhailo Kravtsov, Leonid Surkov

“…Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. …”
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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…The study found that combining soil and climatic variables improved prediction accuracy, with ST, AT, and soil EC being the most influential variables. …”
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Machine Learning-Augmented Triage for Sepsis: Real-Time ICU Mortality Prediction Using SHAP-Explained Meta-Ensemble Models by Hülya Yilmaz Başer, Turan Evran, Mehmet Akif Cifci

“…<b>Background/Objectives:</b> Optimization algorithms are acknowledged to be critical in various fields and dynamical systems since they provide facilitation in identifying and retrieving the most possible solutions concerning complex problems besides improving efficiency, cutting down on costs, and boosting performance. …”
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A review on agrowaste based activated carbons for pollutant removal in wastewater systems by Karinate Valentine Okiy, Joseph Nwabanne Tagbo, Walter Peter Echeng

“…Among these methods, heavy metal adsorption from aqueous solutions by the activated carbons is the most efficient. The deployment of mathematical and machine learning approaches (ANN and novel GMDH algorithms) in optimization of batch and continuous adsorption processes are also highlighted. …”
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Enhancing 4G/LTE Network Path Loss Prediction with PSO-GWO Hybrid Approach by Messaoud Garah, Nabil Boukhennoufa

“…Furthermore, a hybrid optimization model, PSO-GWO, is proposed to improve prediction accuracy. …”
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A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study by Aoyu Li, Jingwen Li, Yishan Hu, Yan Geng, Yan Qiang, Juanjuan Zhao

“…To address the challenges (eg, the curse of dimensionality and increased model complexity) posed by high-dimensional features, we developed a dynamic adaptive feature selection optimization algorithm to identify the most impactful subset of features for classification performance. …”
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Research on 3D Obstacle Avoidance Path Planning for Apple Picking Robotic Arm by Xinyan Chen, Chun Lu, Ziliang Guo, Chengkai Yin, Xuanbo Wu, Xiaolan Lv, Qing Chen

“…The experimental results show that compared to RRT* and IRRT*, the average path cost of the optimization algorithm is reduced by 31.565 mm and 14.935 mm and the average search time is reduced by 7.18 s and 4.33 s. …”
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Research on the cooperative offloading strategy of sensory data based on delay and energy constraints by Peiyan YUAN, Saike SHAO, Ran WEI, Junna ZHANG, Xiaoyan ZHAO

“…The edge offloading of the internet of things (IoT) sensing data was investigated.Multiple edge servers cooperatively offload all or part of the sensing data initially sent to the cloud center, which protects data privacy and improves user experience.In the process of cooperative offloading, the transmission of the sensing data and the information exchange among edge servers will consume system resources, resulting in the cost of cooperation.How to maximize the offloading ratio of the sensing data while maintaining a low collaboration cost is a challenging problem.A joint optimization problem of sensing data offload ratio and cooperative scale satisfying the constraints of network delay and system energy consumption was formulated.Subsequently, a distributed alternating direction method of multipliers (ADMM) via constraint projection and variable splitting was proposed to solve the problem.Finally, simulation experiments were carried out on MATLAB.Numerical results show that the proposed method improved the network delay and energy consumption compared to the fairness cooperation algorithm (FCA), the distributed optimization algorithm (DOA), and multi-subtasks-to-multi-servers offloading scheme (MTMS) algorithm.…”
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Network access and spectrum allocation in next-generation multi-heterogeneous networks by Xiaoqing Dong, Lianglun Cheng, Gengzhong Zheng, Tao Wang

“…By preprocessing of objective function, constraint simplification, and standardization, the complex spectrum allocation problem is transformed into a standard form of the 01 programming problem, and the solution is obtained by an improved Hungarian algorithm. Second, an intelligent optimization algorithm named improved non-dominated sorting genetic algorithm II is proposed, which combines the interference constraints of the primary network and the service quality requirements of the secondary users into the objective value evaluation of non-dominated sorting, and corrects the chromosomes that do not meet the constraints. …”
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Scalable and energy-efficient task allocation in industry 4.0: Leveraging distributed auction and IBPSO. by Qingwen Li, Tang Wai Fan, Lam Sui Kei, Zhaobin Li

“…The main contributions we make are: the design of an auction decentralization algorithm (AOCTA) which allows for an efficient and flexible task distribution in dynamic contexts, the optimization of coalition formation in complex jobs by using IBPSO and improves the efficiency of energy and decreases the cost of computation as well as thorough simulations that show that our proposed method significantly surpasses conventional methods for efficiency, task completion rates in terms of energy usage, task completion rate, and scaling of the system. …”
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Smart estimation of protective antioxidant enzymes’ activity in savory (Satureja rechingeri L.) under drought stress and soil amendments by Amin Taheri-Garavand, Mojgan Beiranvandi, Abdolreza Ahmadi, Nikolaos Nikoloudakis

“…Abstract Savory (Satureja rechingeri L.) is one of Iran’s most important medicinal plants, having low irrigation needs, and thus is considered one of the most valuable plants for cultivation in arid and semi-arid regions, especially under drought conditions. …”
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Multiagent, multitimescale aggregated regulation method for demand response considering spatial–temporal complementarity of user-side resources by Tingzhe Pan, Chao Li, Chen Yang, Zijie Meng, Zongyi Wang, Zean Zhu

“…For the day-ahead timescale, we developed an improved particle swarm optimization (IPSO) algorithm that dynamically adjusts the number of particles based on intraday outcomes to optimize the regulation strategies. …”
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Frequency Regulation Provided by Doubly Fed Induction Generator Based Variable-Speed Wind Turbines Using Inertial Emulation and Droop Control in Hybrid Wind–Diesel Power Systems by Muhammad Asad, José Ángel Sánchez-Fernández

“…Wind energy (WE) is the most adopted renewable energy source due to its technical readiness, competitive cost, and environmentally friendly characteristics. …”
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Finding the Shortest Path with Vertex Constraint over Large Graphs by Yajun Yang, Zhongfei Li, Xin Wang, Qinghua Hu

“…In this paper, we first propose a novel exact heuristic algorithm in best-first search way and then give two optimizing techniques to improve efficiency. …”
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Address Translation in a Compositional Microprogram Control Unit by Alexandr Barkalov, Larysa Titarenko, Oleksandr Golovin, Oleksandr Matvienko

“…The method proposed in the article is based on the adaptation of algorithms for optimizing microprogram automata circuits to the features of CMCUs. …”
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Bayesian Uncertainty Quantification of Reflooding Model With PSO–Kriging and PCA Approach by Ziyue Zhang, Dong Li, Nianfeng Wang, Meng Lei

“…As reflooding is a vital stage to cool the core and prevent serious accidents and uncertainties exist in the important results of the program because of the complexity of the phenomena, IUQ is performed for reflooding models in this study based on Bayesian theory and Markov chain Monte Carlo (MCMC) algorithm. In order to solve the problem of large time costs in sampling and inefficient use of transient sample points, particle swarm optimization (PSO)–Kriging model and principal component analysis (PCA) are adopted in this paper. …”
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Robust design of bicycle infrastructure networks by Christoph Steinacker, Mads Paulsen, Malte Schröder, Jeppe Rich

“…In this paper, we approach the problem from two perspectives: direct optimization methods, which generate near-optimal solutions using operations research techniques, and conceptual heuristics, which offer intuitive and scalable algorithms grounded in network science. …”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…Previous studies have shown high validity and accuracy (up to 100%) of the early detection system of diabetic foot complications using artificial intelligence-based thermography. However, most of these studies focused too much on improving performance and did not pay attention to the computational cost aspect. …”
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Joint Allocation of Power and Subcarrier for Low Delay and Stable Power Line Communication by Zhixiong Chen, Zhihui Yang, Zeng Dou

“…Finally, the performance of the algorithm is compared and analyzed by simulation. The results show that the proposed algorithm can reduce the rate fluctuation and improve the system delay performance and deterministic transmission ability under the condition of ensuring the average rate optimization.…”
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