Machine Learning for Chinese Corporate Fraud Prediction: Segmented Models Based on Optimal Training Windows by Chang Chuan Goh, Yue Yang, Anthony Bellotti, Xiuping Hua

“…Based on a three-stage experiment, we first find that the random forest classifier has the best performance in predicting corporate fraud among 17 machine learning models. We then implement the sliding time window approach to handle population drift, and the optimal training window found demonstrates the existence of population drift in fraud detection and the need to address it for improved model performance. …”
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A multi-objective evolutionary algorithm for detecting protein complexes in PPI networks using gene ontology by Mustafa N. Abbas, David Broneske, Gunter Saake

“…This operator enhances collaboration between the canonical model and the GO-informed mutation strategy, thereby improving the algorithm’s performance. …”
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Optimizing Fall Risk Diagnosis in Older Adults Using a Bayesian Classifier and Simulated Annealing by Enrique Hernandez-Laredo, Ángel Gabriel Estévez-Pedraza, Laura Mercedes Santiago-Fuentes, Lorena Parra-Rodríguez

“…The wrapper method of feature selection using the SA algorithm was applied to optimize the cost function based on the difference of the mean minus the standard deviation of the Area Under the Curve (AUC) of the fall risk classifiers across multiple dimensions. …”
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Optimization of surgical treatment of abdominal hernias in patients with obesity by V. I. Belokonev, V. P. Zakharov, D. B. Grachev, S. Y. Pushkin, Z. V. Kovaleva, D. S. Pushkina

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Enhancing resilience of distribution system under extreme weather: Two-stage energy storage system configuration strategy based on robust optimization by Ye He, Hongyun Fu, Andrew Y. Wu, Hongbin Wu, Ming Ding

“…Finally, a two-stage robust optimization model for the ESS is established to improve DN resilience with the objective of minimizing the comprehensive economic cost of the ESS and the annual comprehensive weighted load loss, which is solved using the column-and-constraint generation algorithm (C&CG). …”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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Improved firefly algorithm–extended Kalman filter–least-square support-vector machine voltage sag monitoring and classification method based on edge computing by Zhu Liu, Xuesong Qiu, Yonggui Wang, Shuai Zhang, Zhi Li

“…Extract characteristic quantities such as average value, duration of sag, minimum sag dispersion characteristics, number of sag phases, and flow direction of disturbance energy. As a model training data set, the least-square support-vector machine method optimized based on the improved firefly algorithm is used to create a multi-level classification model of voltage sag source to realize the classification of voltage sag sources. …”
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Orthogonal Multi‐Swarm Greedy Selection Based Sine Cosine Algorithm for Optimal FACTS Placement in Uncertain Wind Integrated Scenario Based Power Systems by Sunilkumar P. Agrawal, Pradeep Jangir, Arpita, Sundaram B. Pandya, Anil Parmar, Mohammad Khishe, Bhargavi Indrajit Trivedi

“…Flexible AC Transmission System (FACTS) devices, including Static VAR Compensator (SVC), Thyristor‐Controlled Series Compensator (TCSC), and Thyristor‐Controlled Phase Shifter (TCPS), enhance system stability, reduce losses, and lower operational costs when optimally placed. Conventional optimization techniques like Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Moth Flame Optimization (MFO), Gray Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) struggle to balance exploration and exploitation in complex OPF problems, leading to suboptimal solutions. …”
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Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization by Awais Khan, Jung-Yeon Kim, Chomyong Kim, Muhammad Attique Khan, Hyojin Shin, Jiyoung Woo, Yunyoung Nam

“…To optimize feature selection and improve classification performance while reducing computational costs, we employed the tree seed algorithm on the self-attention features of 7-RBNet and 9-RBNet self-attention models. …”
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Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

“…The Superimposed Image combined these heatmaps with the original lesion images, making it clear which parts of the lesions influenced the model’s classification. These results underscore the potential of deep learning models, optimized with the memetic algorithm, to significantly improve skin cancer detection. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…Key AI techniques, including support vector machines (SVMs) (7.90% of studies), decision trees, and gradient-boosting models, offer substantial improvements in cost prediction and resource optimization. …”
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Modeling sunflower yield and soil water–salt dynamics with combined fertilizers and irrigation in saline soils using APSIM and deep learning by Qingfeng Miao, Dandan Yu, Haibin Shi, Zhuangzhuang Feng, Weiying Feng, Zhen Li, José Manuel Gonçalves, Isabel Maria Duarte, Yuxin Li

“…In simulating soil salinity, deep learning models generally outperform machine learning models (EVS ≤ 0.3; R 2 ≤ 0.42), with the deep neural network (DNN (EVS ≤ 0.3; R 2 ≤ 0.82)) algorithm demonstrating the best simulation performance. …”
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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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Optimization of Line Planning by Integrating Ticket Pricing and Seat Allocation Decisions for High-Speed Railway by Xin Shi, Wenliang Zhou, Xiang Li

“…To efficiently solve the model, an improved heuristic algorithm based on the simulated annealing framework combined with a linear passenger flow allocation method is proposed. …”
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Multiobjective optimization of a pressure maintaining ball valve structure based on RSM and NSGA-II by Pengyun Wen, Suling Wang, Jinbo Li, Kangxing Dong, Zhihui Ren, Yanchun Li, Ruyi Qu, Tingting Li

“…In this study, the pressure-bearing structure of the ball valve was optimized, and a theoretical model for its pressure resistance was established. …”
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Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…However, the RF, with hyperparameters optimized by the genetic algorithm, was able to improve the R2 values of the prediction of storage temperature and period to 0.96 and 0.89. …”
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Improved A* Algorithm Based on Artificial Potential Field Method for Global Path Planning of Unmanned Surface Vessels in Complex Environments by Shuxuan Liu, Zhijia Qian, Sunwei Jiang, Quanming Miao

“…In the improved A* algorithm, the search direction was first optimized, simplifying the traditional eight direction search to a “target point attracts four directions” search, significantly reducing the ineffective expansion nodes of the traditional algorithm, reducing algorithm running time, and improving search efficiency; Secondly, on the basis of improving the cost function, the idea of artificial potential field algorithm is integrated, and the repulsive function is introduced. …”
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Innovative real data-driven multi-objective optimization for sustainable energy in Siwa Oasis, Egypt using HYCHOPSO by Hosam Abdelhadi, Ahmed Mohamed Mahmoud, Ebtisam Mostafa Mohamed Saied, Mohamed Ahmed Ebrahim

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SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling by Siqi Xu, Ziqian Yang, Jing Xu, Ping Feng

“…In addition, a multi-hop relational path inference mechanism is introduced to capture long-distance dependencies to improve the depth of user interest modeling. Experiments on the Amazon-Book and Last-FM datasets show that SKGRec significantly outperforms several state-of-the-art recommendation algorithms on the Recall@20 and NDCG@20 metrics. …”
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Forecasting Renewable energy and electricity consumption using evolutionary hyperheuristic algorithm by Yang Cao, Jun Yu, Rui Zhong, Masaharu Munetomo

“…The configuration of optimal parameters for these models typically requires optimization algorithms, but conventional algorithms may struggle with fixed search patterns and limited robustness. …”
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