A Metaheuristic Framework for Cost-Effective Renewable Energy Planning: Integrating Green Bonds and Fiscal Incentives by Juan D. Saldarriaga-Loaiza, Johnatan M. Rodríguez-Serna, Jesús M. López-Lezama, Nicolás Muñoz-Galeano, Sergio D. Saldarriaga-Zuluaga

“…To do this, we use three optimization techniques to identify solutions that lower electricity generation costs: Teaching Learning, Harmony Search, and the Shuffled Frog Leaping Algorithm. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Furthermore, the Ordered Weighted Averaging (OWA) algorithm and the Partical Swarm Optimization-Support Vector Machine (PSO-SVM) model were combined to simulate future GDV scenarios for 2030–2050 under three development preferences: environment oriented, status quo, and economically oriented. …”
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Studying the influence of correction codes on coherent reception of M-PSK signals in the presence of noise and harmonic interference by V. D. Nguyen

“…The methods of statistical radio engineering, optimal signal reception theory and computer simulation modeling were used.Results. …”
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Data-Driven ANN-Based Predictive Modeling of Mechanical Properties of 5Cr-0.5Mo Steel: Impact of Composition and Service Temperature by Muhammad Ishtiaq, Saurabh Tiwari, Molakatala Nagamani, Sung-Gyu Kang, Nagireddy Gari Subba Reddy

“…The ANN model’s findings offer valuable insights for researchers and designers, aiding in developing steel components with optimized properties. …”
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Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data by N. Mandal, P. Das, K. Chanda, K. Chanda

“…The most effective machine learning (ML) algorithms among convolutional neural network (CNN), support vector regression (SVR), extra trees regressor (ETR) and stacking ensemble regression (SER) models are evaluated at each grid cell to achieve optimal reproducibility. …”
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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal. by Susana Lavado, Eduardo Costa, Niclas F Sturm, Johannes S Tafferner, Octávio Rodrigues, Pedro Pita Barros, Leid Zejnilovic

“…Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. …”
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Enhancing cotton irrigation with distributional actor–critic reinforcement learning by Yi Chen, Meiwei Lin, Zhuo Yu, Weihong Sun, Weiguo Fu, Liang He

“…This study introduces a novel intelligent irrigation approach based on distributional reinforcement learning, ensuring that the algorithm simultaneously considers weather, soil, and crop conditions to make optimal irrigation decisions for long-term benefits. …”
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A Dual-Variable Selection Framework for Enhancing Forest Aboveground Biomass Estimation via Multi-Source Remote Sensing by Dapeng Chen, Hongbin Luo, Zhi Liu, Jie Pan, Yong Wu, Er Wang, Chi Lu, Lei Wang, Weibin Wang, Guanglong Ou

“…A dual-variable selection strategy based on SHapley Additive exPlanations (SHAP) was developed, and a genetic algorithm (GA) was used to optimize the parameters of five machine learning models—elastic net (EN), least absolute shrinkage and selection operator (Lasso), support vector regression (SVR), Random Forest (RF), and Categorical Boosting (CatBoost)—to estimate the AGB of <i>Pinus kesiya</i> var. …”
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Enhancing grid-connected PV-EV charging station performance through a real-time dynamic power management using model predictive control by Aziz Watil, Hamid Chojaa

“…This paper presents a novel station manager algorithm for grid-connected PV-EV charging stations, designed to address key challenges in current systems. …”
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Risk prediction and analysis of gallbladder polyps with deep neural network by Kerong Yuan, Xiaofeng Zhang, Qian Yang, Xuesong Deng, Zhe Deng, Xiangyun Liao, Weixin Si

“…This predictive model can be employed to differentiate the nature of polyps before surgery, enhancing diagnostic accuracy. …”
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Robust Sandstorm Image Restoration via Adaptive Color Correction and Saturation Line Prior-Based Dust Removal by Shan Zhou, Fei Shi, Zhenhong Jia, Guoqiang Wang, Jian Huang

“…Finally, the atmospheric scattering model is employed for comprehensive image restoration, ensuring that color correction and dust removal are optimized. …”
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Nodal Carbon Emission Factor Prediction for Power Systems Based on MDBO-CNN-LSTM by Lihua Zhong, Feng Pan, Yuyao Yang, Lei Feng, Haiming Shao, Jiafu Wang

“…In this study, we address these limitations by improving population initialization, search mechanisms, and iteration strategies and developing a hybrid strategy Modified Dung Beetle Optimization (MDBO) algorithm. …”
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A Stackelberg Trust-Based Human–Robot Collaboration Framework for Warehouse Picking by Yang Liu, Fuqiang Guo, Yan Ma

“…An iterative Stackelberg trust strategy generation (ISTSG) algorithm is designed to achieve the optimal long-term collaboration benefits between humans and robots, which is solved by the Bellman equation. …”
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Bridging the Gap: A Review of Machine Learning in Water Quality Control by Herlina Abdul Rahim, Nur Athirah Syafiqah Noramli, Indrabayu

“…Emerging solutions like federated learning (35% accuracy improvement in pan-African E. coli prediction) and explainable AI (SHAP-guided nitrate models) address these barriers. …”
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Predicting metabolic dysfunction associated steatotic liver disease using explainable machine learning methods by Yihao Yu, Yuqi Yang, Qian Li, Jing Yuan, Yan Zha

“…The random forest (RF) model performed best in discriminative ability among 6 ML models, and the optimal 10-feature RF model was finally chosen. …”
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Multi-Agent Mapping and Tracking-Based Electrical Vehicles with Unknown Environment Exploration by Chafaa Hamrouni, Aarif Alutaybi, Ghofrane Ouerfelli

“…When rapid deliveries are required, the algorithm prioritizes faster routes, whereas, for flexible schedules, it optimizes energy conservation. …”
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From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…Additionally, it outlines future challenges and opportunities, emphasizing the need for improved algorithms, data standardization, and interdisciplinary collaboration. …”
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Predicting Pathological Complete Response Following Neoadjuvant Therapy in Patients With Breast Cancer: Development of Machine Learning–Based Prediction Models in a Retrospective S... by Chun-Chi Lai, Cheng-Yu Chen, Tzu-Hao Chang

“…ConclusionsThis study suggests that incorporating breast sonography into models with clinical and laboratory data may modestly improve pCR prediction. …”
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Сontrol of Intelligent Transport System in Minsk by D. V. Kapskiy, D. V. Navoy, P. A. Pegin

“…The paper considers algorithms for searching a maximum traffic volume of road vehicles in a traffic light cycle with a distributed intensity pulse and optimization of shifts under coordinated traffic flow control. …”
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Interactive online learning method for students based on artificial intelligence by Cizhang Li, Wenfen Yin

“…This study proposes a novel approach that integrates the Dwarf Mongoose Optimization (DMO) algorithm with a Gated Recurrent Unit (GRU) neural network to develop an AI-powered interactive online learning model. …”
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