Coupling a Bat Algorithm with XGBoost to Estimate Reference Evapotranspiration in the Arid and Semiarid Regions of China by Yixiu Han, Jianping Wu, Bingnian Zhai, Yanxin Pan, Guomin Huang, Lifeng Wu, Wenzhi Zeng

“…Accurate estimation of reference evapotranspiration (ETo) is key to agricultural irrigation scheduling and water resources management in arid and semiarid areas. This study evaluates the capability of coupling a Bat algorithm with the XGBoost method (i.e., the BAXGB model) for estimating monthly ETo in the arid and semiarid regions of China. …”
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A systematic review of reinforcement learning-based control for microgrids: trends, challenges, and emerging algorithms by A. V. Waghmare, V. P. Singh, T. Varshney, P. Sanjeevikumar

“…Modern day control techniques are getting attention by researchers for optimal control and management of microgrids, as it is found in many articles that classical control techniques are short-falling in adaptability in different environments, data handling and data driven decision making. …”
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Development and Comparison of Interrupt-Based and Analog-to-Digital Converter Algorithms for Seed Counting in Precision Planters by A. Ghaffarnezhad, H. Navid, H. Karimi

“…In response to these challenges, researchers are actively exploring various solutions, employing diverse approaches such as the development of different algorithms and the utilization of alternative hardware configurations. …”
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Validation of a teaching model instrument for university education in Ecuador through an artificial intelligence algorithm by Jenniffer Sobeida Moreira-Choez, Tibisay Milene Lamus de Rodríguez, Aracelly Fernanda Núñez-Naranjo, Ángel Ramón Sabando-García, María Belén Reinoso-Ávalos, Cynthia Michel Olguín-Martínez, Daniel Omar Nieves-Lizárraga, Julieta Elizabeth Salazar-Echeagaray

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Overlapping community-based fair influence maximization under a multi-transformation optimization algorithm by Chunfeng Jiang, Zegang Niu, Jingru Qu, Yulan Zhao, Amin Rezaeipanah

“…It employs a multi-transformation evolutionary framework that optimizes multiple transformations simultaneously, ensuring scalability and convergence. The algorithm adapts to different transformations without the need for manual selection, allowing it to efficiently explore the solution space. …”
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A Semiactive and Adaptive Hybrid Control System for a Tracked Vehicle Hydropneumatic Suspension Based on Disturbance Identification by Shousong Han, Zhiqiang Chao, Xiangbo Liu

“…Optimal scheduling of the semiactive hybrid damping control gain (csky, cground, chybrid) and self-adaptive control gain (cv) under different disturbances were realized by exploiting the particle swarm multiobjective optimization algorithm. …”
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Virtual Validation and Uncertainty Quantification of an Adaptive Model Predictive Controller-Based Motion Planner for Autonomous Driving Systems by Mohammed Irshadh Ismaaeel Sathyamangalam Imran, Satyesh Shanker Awasthi, Michael Khayyat, Stefano Arrigoni, Francesco Braghin

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Intelligent anti-jamming decision algorithm of bivariate frequency hopping pattern based on ET-PPO by Yibo CHEN, Zhijin ZHAO

“…In order to further improve its anti-interference ability in complex electromagnetic environment, a PPO algorithm based on weighted importance sampling and eligibility traces (ET-PPO) was proposed.On the basis of the traditional frequency hopping pattern, time-varying parameters were introduced, and the bivariate frequency hopping pattern decision problem was modeled as a Markov decision problem through the construction of the state-action-reward triple.Aiming at the high variance problem of the sample update method of an actor network of the PPO algorithm, weighted importance sampling was introduced to reduce the variance, and the action selection strategy of Beta distribution was used to enhance the stability of the learning stage.Aiming at the problem of slow convergence speed of the evaluator network, the eligibility trace method was introduced, which better balanced the convergence speed and the global optimal solution.The algorithm comparison simulation results in different electromagnetic interference environments show that ET-PPO has better adaptability and stability, and has better performance against obstruction interference and sweep frequency interference.…”
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D3QN-based collaborative offloading algorithm for vehicular networks assisted by digital twins by CHEN Geng, SONG Zhenghan, XIA Conghui, ZENG Qingtian

“…Next, based on task decomposability, two types of task models were established, and a hybrid offloading strategy was devised to accurately adapt to dynamic real-world demands. Furthermore, a D3QN-based collaborative offloading algorithm for vehicle clusters was developed, utilizing a dual-network architecture to decouple action and target evaluations, thereby suppressing <italic>Q</italic>-value bias, accelerating policy convergence, and achieving a balance between utility and latency. …”
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Algorithm-Based Real-Time Analysis of Heart Rate Measures in HIIT Training: An Automated Approach by Sergio Amat, Sonia Busquier, Carlos D. Gómez-Carmona, Manuel Gómez-López, José Pino-Ortega

“…The algorithm detects local maxima and minima in the heart rate signals recorded during HIIT sessions and calculates ascending and descending slopes, as well as intermediate averages, to evaluate cardiovascular response and recovery. …”
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Versatile machine learning algorithms for FTIR spectroscopy: differentiating crosslinked and non-crosslinked gelatin samples by Juliana Rincón-López, Eliana Álvarez-Valdés, Daniela Velez-Arango, Estefanía Rojas Zuleta, Leidy Yuliana Vargas Soto, Liliana Lellesch, Victor Alonso García Londoño, Milton Rosero-Moreano, Gonzalo Taborda-Ocampo

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Energy efficiency of heating equipment and resources in the implementation and adaption of lean manufacturing tools LLC TATNEFT-AZS center by L. R. Mukhametova, I. G. Akhmetova, D. A. Zaripova, A. R. Nurislamova

“…Describe the essence of the technology, consider the problems, the complexity of implementation and propose an algorithm for introducing the technology and involving each employee in the process of optimizing the business and maximizing customer focus. …”
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Advanced Supply Chain Management Using Adaptive Serial Cascaded Autoencoder with LSTM and Multi-Layered Perceptron Framework by Aniruddha Deka, Parag Jyoti Das, Manob Jyoti Saikia

“…This paper explores financial risk assessment in supply chain management using advanced deep learning techniques on big data. The Adaptive Serial Cascaded Autoencoder (ASCA), combined with Long Short-Term Memory (LSTM) and Multi-Layered Perceptron (MLP), is used to evaluate financial risks. …”
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Improved Energy Efficient Anytime Optimistic Algorithm for PEGASIS to Extend Network Lifetime in Homogeneous and Heterogeneous Networks by Tadele A. Abose, Venumadhav Tekulapally, Samuel T. Daka, Diriba C. Kejela, Alemayehu E. Duguma, Desalegn T. Degaga

“…The proposed algorithm demonstrates a 40% improvement across all evaluated features compared to existing algorithms.…”
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Enhancing power efficiency in BLDC motor drives for drones using multiview learning with hybrid optimization algorithms by Anushree Gopalakrishnan, Rani Thottungal

“…Employing multi-view learning techniques, it evaluates various performance metrics such as torque speed and power, revealing substantial improvements over the existing methods. …”
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A bi-subpopulation coevolutionary immune algorithm for multi-objective combinatorial optimization in multi-UAV task allocation by Xi Chen, Yu Wan, Jingtao Qi, Zipeng Zhao, Yirun Ruan, Jun Tang

“…Therefore, this paper constructs a Multi-objective Combinatorial Optimization in Multi-UAV Task Allocation Problem (MCOTAP) model, and proposes a Bi-subpopulation Coevolutionary Immune Algorithm (BCIA). The two coevolutionary mechanisms improve the lower limit of population diversity, and the evolutionary strategy pool integrating multiple strategies and the adaptive strategy selection mechanism enhance the local search ability in the late evolution. …”
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Research of UAV 3D path planning based on improved Dwarf mongoose algorithm with multiple strategies by Lixin Mu, Wenhui Liu, Haocheng Wang, Yu Zhang

“…Abstract Unmanned Aerial Vehicles (UAVs) consistently encounter complex operational environments during task execution. To enhance UAV adaptability in such environments, improve rapid and efficient path planning capabilities, and reduce operational costs, this paper proposes a 3D UAV path planning algorithm based on an improved Dwarf Mongoose Optimization (DMO) algorithm enhanced with multiple strategies. …”
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A Machine Learning Approach to Evaluate the Performance of Rural Bank by Jun Wei, Tao Ye, Zhe Zhang

“…Aiming at the characteristics of commercial bank data, this paper proposes an adaptively reduced step size gradient boosting regression tree algorithm for bank performance evaluation. …”
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The Impact of an Adaptive mHealth Intervention on Improving Patient-Provider Health Care Communication: Secondary Analysis of the DIAMANTE Trial by Lynn Leng, Marvyn R Arévalo Avalos, Adrian Aguilera, Courtney R Lyles

“…MethodsThis study used data from the DIAMANTE (Diabetes and Mental Health Adaptive Notification Tracking and Evaluation) trial, a prospective, randomized controlled trial that varied SMS text messaging strategies to encourage physical activity to support both mental and physical health for patients with diabetes and depression. …”
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Enhancing Wind Turbine Power Output Estimation Using Causal Inference and Adaptive Neuro-Fuzzy Inference System ANFIS by Ahmed A. Mostfa, Nawfal A. Zakar, Rasha Raad Al-Mola, Abdel-Nasser Sharkawy

“…To meet the demand for renewable energy at the lowest cost, wind energy became the target of machine learning algorithms and was employed to predict the output power of wind turbines. …”
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