Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

“…Compared to a baseline model from the literature, O-LGB achieved significant improvements in predictive performance. For compressive strength, it reduced the Mean Absolute Error (MAE) by 87.69% and the Root Mean Squared Error (RMSE) by 71.93%. …”
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Surface Reconstruction Planning with High-Quality Satellite Stereo Pairs Searching by Jinwen Li, Guangli Ren, Youmei Pan, Jing Sun, Peng Wang, Fanjiang Xu, Zhaohui Liu

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A Biased–Randomized Iterated Local Search with Round-Robin for the Periodic Vehicle Routing Problem by Juan F. Gomez, Antonio R. Uguina, Javier Panadero, Angel A. Juan

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A deep dive into artificial intelligence with enhanced optimization-based security breach detection in internet of health things enabled smart city environment by S Jayanthi, Sodagudi Suhasini, N. Sharmili, E. Laxmi Lydia, V. Shwetha, Bibhuti Bhusan Dash, Mrinal Bachute

“…For the selection of the feature process, the proposed SADDBN-AMOA model designs a slime mould optimization (SMO) model to select the most related features from the data. …”
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Multi-user joint task offloading and resource allocation based on mobile edge computing in mining scenarios by Siqi Li, Weidong Li, Wanbo Zheng, Yunni Xia, Kunyin Guo, Qinglan Peng, Xu Li, Jiaxin Ren

“…To evaluate the effectiveness of the proposed method, we compare it with five baseline algorithms: the improved grey wolf optimizer metaheuristic algorithm, the traditional genetic algorithm, the binary offloading decision mechanism, the partial non-cooperative mechanism, and the fully local execution mechanism. …”
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Secure THz Communication in 6G: A Two-Stage DRL Approach for IRS-Assisted NOMA by Muhammad Shahwar, Manzoor Ahmed, Touseef Hussain, Muhammad Sheraz, Wali Ullah Khan, Teong Chee Chuah

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Short‐term electric power and energy balance optimization scheduling based on low‐carbon bilateral demand response mechanism from multiple perspectives by Juan Li, Yonggang Li, Huazhi Liu

“…The enhanced decision tree classifier (EDTC) algorithm is used to predict the electricity consumption behavior of transferable load (TL) users, and an improved particle swarm optimization (PSO) algorithm with “ε‐greedy” strategy is proposed to solve this model. …”
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The Impact of the Natural Grass-Growing Model on the Development of Korla Fragrant Pear Fruit, as Well as Its Influence on Post-Harvest Sugar Metabolism and the Expression of Key E... by Mingyang Yu, Lanfei Wang, Yan Chen, Weifan Fan, Hao Wang, Kailu Guo, Shutian Tao, Xin Gong, Jianping Bao

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Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…Aiming to reduce the maximum electric field strength of the reactor, this paper proposes a hybrid surrogate model that combines Radial Basis Function Neural Network (RBFNN) and the Kriging model to optimize the configuration of grading rings. First, the sparrow search algorithm is used to optimize the hyperparameters of the RBFNN. …”
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A spherical fuzzy WASPAS approach to prioritize the factors enhancing the effectiveness of physical education classroom teaching by Yuhan Gao, Ali Yu

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Hyperspectral Anomaly Detection by Spatial–Spectral Fusion Based on Extreme Value-Entropy Band Selection and Cauchy Graph Distance Optimization by Song Zhao, Yali Lv, Wen Zhang, Lijun Wang, Zhiru Yang, Gaofeng Ren, Bin Wang, Xiaobin Zhao, Tongwei Lu, Jiayao Wang, Wei Li

“…This algorithm combines spectral extremum detection with information entropy filtering to select the most representative bands by considering multidimensional information. …”
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Construction and application of a digital twin model for multi-objectiveoptimization of intelligent tape conveyor system by Wei CHEN, Jingzhao LI, Qing SHI, Jichao LIU, Huashun LI

“…Moreover, forecast values of sweep force at the current moment help formulate the dispatch plan for the cleaning mechanism in the next moment, thus ensuring precise control of the physical model. The Improved Whale Optimization Algorithm (IWOA) is employed to optimize parameters in this blueprint, facilitating real-time scheduling by rapidly converging to the global optimum. …”
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Accelerating Grover Adaptive Search: Qubit and Gate Count Reduction Strategies With Higher Order Formulations by Yuki Sano, Kosuke Mitarai, Naoki Yamamoto, Naoki Ishikawa

“…Grover adaptive search (GAS) is a quantum exhaustive search algorithm designed to solve binary optimization problems. …”
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Estimating forest aboveground carbon sink based on landsat time series and its response to climate change by Kun Yang, Kai Luo, Jialong Zhang, Bo Qiu, Feiping Wang, Qinglin Xiao, Jun Cao, Yunrun He, Jian Yang

“…We found that (1) GA can effectively improve the estimation accuracy of RF, the R 2 can be improved by up to 34.8%, and the optimal GA-RF model R 2 is 0.83. (2) The CSI of Pinus densata in Shangri-La was 0.45–0.72 t C·hm− 2 from 1987 to 2017. (3) Precipitation has the most significant effect on CSI. …”
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Sustainable Self-Training Pig Detection System with Augmented Single Labeled Target Data for Solving Domain Shift Problem by Junhee Lee, Heechan Chae, Seungwook Son, Jongwoong Seo, Yooil Suh, Jonguk Lee, Yongwha Chung, Daihee Park

“…Overcoming this limitation through large-scale labeling presents considerable burdens in terms of time and cost. To address the degradation issue, this study proposes a self-training-based domain adaptation method that utilizes a single label on target (SLOT) sample from the target domain, a genetic algorithm (GA)-based data augmentation search (DAS) designed explicitly for SLOT data to optimize the augmentation parameters, and a super-low-threshold strategy to include low-confidence-scored pseudo-labels during self-training. …”
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A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

“…Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. …”
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Reconstruction of Highway Vehicle Paths Using a Two-Stage Model by Weifeng Yin, Junyong Zhai, Yongbo Yu

“…In the first stage, a Gaussian Mixture Model (GMM) is integrated into a path choice model to estimate the mean and standard deviation of travel times for each road segment, utilizing an improved Expectation Maximization (EM) algorithm. In the second stage, based on the estimated time parameters, path choice prior probabilities and observed data are combined using maximum likelihood estimation to infer the most probable paths among candidate routes. …”
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A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools by Saad Javed Cheema, Masoud Karbasi, Gurjit S. Randhawa, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal, Farhat Abbas, Qamar Uz Zaman, Aitazaz A. Farooque

“…A machine learning approach using XGBoost, optimized with the Chaos Game algorithm (CGO-XGBoost), was employed to predict Kc. …”
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An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance by Abhijeet Das

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Integrative Path Planning for Multi-Rotor Logistics UAVs Considering UAV Dynamics, Energy Efficiency, and Obstacle Avoidance by Kunpeng Wu, Juncong Lan, Shaofeng Lu, Chaoxian Wu, Bingjian Liu, Zenghao Lu

“…Since UAVs’ energy storage capacity is generally low, it is essential to reduce energy costs to improve their system’s energy efficiency. …”
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