Daily runoff forecasting using novel optimized machine learning methods by Peiman Parisouj, Changhyun Jun, Sayed M. Bateni, Essam Heggy, Shahab S. Band

“…This study addresses these challenges by introducing a novel bio-inspired metaheuristic algorithm, Artificial Rabbits Optimization (ARO), integrated with various machine learning (ML) models for runoff forecasting in the Carson and Chehalis River basins. …”
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Optimization Techniques on Quantum and Classical Systems: A Comprehensive Comparative Study by Shaik Hussain, Rajitha Morampudi, Priyamvada K., Bhargavi R. Naveena

“…This study compares Particle Swarm Optimization (PSO), Moth Flame Optimization (MFO), and Genetic Algorithm (GA) on three platforms : a local computer, a local computer with quantum integration, and an IBM quantum machine. …”
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Entire aerial-aquatic trajectory modeling and optimization for trans-medium vehicles by Teng Long, Nianhui Ye, Baoshou Zhang, Jingliang Sun, Renhe Shi

“…Simultaneously, several constraints, i.e., the max impact load, trajectory height, etc., are involved in the optimization problem. Rather than directly optimizing by a heuristic algorithm, a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem. …”
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Optimization of Toolpath Planning and CNC Machine Performance in Time-Efficient Machining by Arbnor Pajaziti, Orlat Tafilaj, Afrim Gjelaj, Besart Berisha

“…We propose a method that integrates advanced algorithms to identify and eliminate redundant movements, optimize the toolpaths, and improve the machining strategies. …”
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Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

“…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
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Solution Approach to the Minimum Spanning Tree Problem in Tsukamoto Fuzzy and Fermantean Fuzzy Environments by Desli de Haas, Citra Palembang, Aziz Rumakefing

“…Solving Fuzzy Minimum Spanning Tree (FFMST) and Fuzzy Tsukamoto using modified Prim Algorithm for Undirected Graphs and modified Optimal Branching Algorithm for Directed Graphs in FFN environment. …”
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Dynamic Coal Flow-Based Energy Consumption Optimization of Scraper Conveyor by Qi Lu, Yonghao Chen, Xiangang Cao, Tao Xie, Qinghua Mao, Jiewu Leng

“…Conversely, simultaneously increasing both chain and drum speeds helps to maintain lump coal size. The final optimization scheme demonstrates this balance—achieving improved energy efficiency at the cost of increased coal fragmentation. …”
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MODEL FOR THE FORMATION OF A PROJECT TEAM COMPOSITION BASED ON DISCRETE OPTIMIZATION METHODS by S.M. Beketov, M.V. Dergachev, S.G. Redko

“…The problem lies in the need to improve the efficiency and effectiveness of projects by optimizing the composition of teams. …”

Optimization mechanism of attack and defense strategy in honeypot game with evidence for deception by Lihua SONG, Yangyang JIANG, Changyou XING, Guomin ZHANG

“…Using game theory to optimize honeypot behavior is an important method in improving defender’s trapping ability.Existing work tends to use over simplified action spaces and consider isolated game stages.A game model named HoneyED with expanded action spaces and covering comprehensively the whole interaction process between a honeypot and its adversary was proposed.The model was focused on the change in the attacker’s beliefs about its opponent’s real identity.A pure-strategy-equilibrium involving belief was established for the model by theoretical analysis.Then, based on the idea of deep counterfactual regret minimization (Deep-CFR), an optimization algorithm was designed to find an approximate hybrid-strategy-equilibrium.Agents for both sides following hybrid strategies from the approximate equilibrium were obtained.Theoretical and experimental results show that the attacker should quit the game when its belief reaches a certain threshold for maximizing its payoff.But the defender’s strategy is able to maximize the honeypot’s profit by reducing the attacker’s belief to extend its stay as long as possible and by selecting the most suitable response to attackers with different deception recognition abilities.…”
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Wireless Energy Transmission Link Optimization considering Microwave Energy Relay by Yuanming Song, Yajie Liu, Xu Yang

“…Based on the idea of microwave energy relay transmission, the paper constructs a microwave wireless transmission link planning model which considers power relay and uses the evolutionary algorithm to solve the wireless transmission link planning model with two-layer optimization. …”
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Shape optimization of non-uniform parametric piezoelectric energy harvester beam by Milad Hasani, Hossein Shahverdi

“…The model, validated through finite element method (FEM) simulations and experimental data, enables rapid analysis and optimization of PEHs. The Nelder-Mead optimization algorithm was employed to enhance power generation performance across three cross-sectional configurations: rectangular, trapezoidal, and quadratic. …”
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Multi-Attribute Collaborative Optimization for Multimodal Transportation Based on User Preferences by Youpeng Lu, Gang Gao

“…In terms of solution methods, an improved Genetic Algorithm (GA) and Aptenodytes Forsteri Optimization (AFO) hybrid algorithm (GA-AFO) is proposed, which introduces GA to generate a high-quality initial population to accelerate convergence. …”
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Research on pose estimation algorithm of non-cooperative target tracked vehicles based on PnP model by Zhigang Ren, Xinagjun Tang, Guoquan Ren, Dinghai Wu

“…Finally, the pose equation is solved by finding the local minimum of the cost function through algebraic optimization, thus avoiding convergence issues in iterative optimization. …”
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CALCULATION METHODS OF OPTIMAL ADJUSTMENT OF CONTROL SYSTEM THROUGH DISTURBANCE CHANNEL by I. M. Golinko, G. G. Kulakov, Yu. M. Kovrigo

“…As the automatic control system optimization with proportional plus reset controllers on disturbance channel is an unimodal task, the main algorithm of optimization is realized by Hooke – Jeeves method. …”
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Stability Evaluation Method for Rock Slope-Anchorage Systems Based on Genetic Algorithms and Discrete Element Analysis by Peng Xia, Bowen Zeng, Yiheng Pan

“…The findings indicate that (1) the proposed evaluation method effectively accounts for the interaction between the anchorage structure and the rock slope, ensuring accurate results; (2) the method leverages the discrete element numerical model to quantitatively assess deformation and stress distribution within the system; (3) the integration of genetic algorithms significantly enhances the efficiency of identifying the most representative numerical model, and thereby the efficiency of stability evaluation is improved; and (4) the evaluation framework is capable of performing dynamic analyses of the stability evolution throughout the entire operational lifecycle of the rock slope anchorage system.…”
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Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems by Eric Yanchenko, Thomas M. Chappell, Anders S. Huseth

“…In this study, a Bayesian optimization (BO) algorithm was used to learn more about the optimal distribution of a fine-scale trap network targeting Helicoverpa zea (Boddie), a significant agricultural pest across North America. …”
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Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

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Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer by César Feniou, Muhammad Hassan, Baptiste Claudon, Axel Courtat, Olivier Adjoua, Yvon Maday, Jean-Philip Piquemal

“…However, practical implementations on current quantum processing units (QPUs) are challenging due to the noisy evaluation of a polynomially scaling number of observables, undertaken for operator selection and high-dimensional cost function optimization. We introduce an adaptive algorithm using analytic, gradient-free optimization, called Greedy Gradient-free Adaptive VQE (GGA-VQE). …”
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Optimizing concrete strength: How nanomaterials and AI redefine mix design by Dan Huang, Guangshuai Han, Ziyang Tang

“…XGB was identified as the most effective ML algorithm for predicting compressive strength among others in this study (R2=0.974). …”
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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…Additionally, the proposed phased artificial lemming algorithm (ALA) outperforms traditional optimization algorithms in terms of solution quality. …”
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