Energy management of compound power supply based on grey wolf algorithm by Hui YI, Hui CHEN

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Stochastic artificial intelligence models for water resources management: innovative riverflow estimation amidst uncertainty by Mojtaba Poursaeid

“…The primary model used was RT, a method that uses Bayesian optimization and stochastic search algorithms to provide an accurate estimate of the maximum flow within a river. …”
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Deep neural networks and fractional grey lag Goose optimization for music genre identification by Yuanye Tian

“…A fractional-order-based variant of the Grey Lag Goose Optimization (FGLGO) algorithm is used to optimize the parameters of ResNeXt to boost the performance of the model. …”
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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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A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

“…Machine learning (ML) based models have garnered attention in the realm of predictive healthcare, with ensemble methods, in particular, bolstering algorithms to improve classification performance. …”
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Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…The use of CBO ensures efficient convergence with minimal parameter tuning, making the model suitable for large-scale datasets compared to conventional optimizers, including Adam, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
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Detection of Hepatocellular Carcinoma Using Optimized miRNA Combinations and Interpretable Machine Learning Models by Zhengwu Long, Lisheng Zhang

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Development of an optimized deep learning model for predicting slope stability in nano silica stabilized soils by Ishwor Thapa, Sufyan Ghani, Prabhu Paramasivam, Mitiku Adare Tufa

“…The results show that RNN-CNN-LSTM, optimized through OPTUNA algorithms, overcomes conventional machine learning models and achieves an accuracy of 99.4% on unseen test data, supported by stable validation trends and robust predictive 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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Bi-objective green supply chain network design under disruption risk through an extended NSGA-II algorithm by Xiaoqing Wang, Gang Chen, Song Xu

“…Moreover, we propose an extended elitist non-dominated sorting genetic algorithm (NSGA-II) to solve the bi-objective optimization model. …”
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DyEHS: An Integrated Dynamo–EPANET–Harmony Search Framework for the Optimal Design of Water Distribution Networks by Francesco De Paola, Giuseppe Speranza, Giuseppe Ascione, Nunzio Marrone

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Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment by Vikas K. Soman, V. Natarajan

“…This paper presents a novel Crayfish Optimization based Pixel Selection using Block Scrambling Based Encryption Approach (CFOPS-BSBEA) technique that offers a unique solution to improve security in cloud environments. …”
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Robust Adaptive Path Tracking Control Scheme for Safe Autonomous Driving via Predicted Interval Algorithm by Cong Phat Vo, Jungeun Lee, Jeong Hwan Jeon

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Integrating hybrid bald eagle crow search algorithm and deep learning for enhanced malicious node detection in secure distributed systems by Feras Mohammed Al-Matarneh

“…Meanwhile, the convolutional sparse autoencoder (CSAE) model detects malicious nodes. Finally, the dung beetle optimization (DBO) method is employed for the parameter range of the CSAE method. …”
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A Lyapunov Optimization-Based Approach to Autonomous Vehicle Local Path Planning by Ziba Arjmandzadeh, Mohammad Hossein Abbasi, Hanchen Wang, Jiangfeng Zhang, Bin Xu

“…This paper presents a novel approach using Lyapunov Optimization (LO) for local path planning in AVs. The proposed LO model is benchmarked against two conventional methods: model predictive control and a sampling-based approach. …”
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Study on User Fraud Identification of PV Expansion Based on a Bottom-Up Approach of a DELM Algorithm Improved by SSA for a Power Distribution Network by Wang Jinpeng, Wei Haojie, Dou Shunyao, Jeremy-Gillbanks, Zhao Xin

“…Next, a Sparrow Search Algorithm (SSA) was applied to optimize the weight parameters of the Deep Extreme Learning Machine (DELM). …”
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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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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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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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A new method of task aggregation and optimization allocation for multiple groups collaborative task networks by WeiWei Du, XiaoWei Chen

“…Abstract As task diversity and inter-task relationship complexity grow, optimal formation power allocation is key to improving task execution efficiency. …”
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