A constructal theory framework for optimizing HRSG design: Enhancing thermal performance and cost-effectiveness by Morteza Mehrgoo, Majid Amidpour

“…This study utilizes Constructal Theory and genetic algorithms to formulate a comprehensive optimization framework for selecting the appropriate type of Heat Recovery Steam Generator (HRSG) in combined cycle power plants. …”
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Cutting-Edge Stochastic Approach: Efficient Monte Carlo Algorithms with Applications to Sensitivity Analysis by Ivan Dimov, Rayna Georgieva

“…This knowledge helps in identifying critical factors that significantly influence the model’s outcomes and can guide efforts to improve the accuracy and reliability of predictions. …”
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Intelligent pattern design using 3D modelling technology for urban sculpture designing by Wei Wan

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Energy, exergy and economic optimization application of integrated dual-loop organic rankine cycle: A case of shopping mall power plant by Muhammed Taha TOPCU, Alperen TOZLU, Kadir BİLEN

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DGSS-YOLOv8s: A Real-Time Model for Small and Complex Object Detection in Autonomous Vehicles by Siqiang Cheng, Lingshan Chen, Kun Yang

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Prediction of Water Quality in Agricultural Watersheds Based on VMD-GA-LSTM Model by Yuxuan Luo, Xianglan Meng, Yutong Zhai, Dongqing Zhang, Kaiping Ma

“…In order to solve the nonlinear and non-stationary characteristics of water quality data, this paper proposes a combined model based on variational modal decomposition and genetic algorithm optimization of long short-term memory networks (VMD-GA-LSTM) for agricultural watershed water quality prediction. …”
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Predicting compressive strength of concrete at elevated temperatures and optimizing its mixture proportions by Jinjun Xu, Han Wang, Wenjun Wu, Lang Lin, Yong Yu

“…The Cuckoo search algorithm was then employed to optimize mix designs, balancing high-temperature strength, cost and sustainability. …”
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Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks by Aida Issembayeva, Oleksandr Kuznetsov, Anargul Shaushenova, Ardak Nurpeisova, Gabit Shuitenov, Maral Ongarbayeva

“…While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. …”
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DeepDate: A deep fusion model based on whale optimization and artificial neural network for Arabian date classification. by Nour Eldeen Mahmoud Khalifa, Jiaji Wang, Mohamed Hamed N Taha, Yudong Zhang

“…<h4>Method</h4>In this paper, a deep fusion model based on whale optimization and an artificial neural network for Arabian date classification is proposed. …”
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A Review of Quantitative Characterization of Phase Interface Dynamics and Optimization of Heat Transfer Modeling in Direct Contact Heat Transfer by Mingjian Wang, Jianxin Xu, Shibo Wang, Hua Wang

“…Many scholars have focused their research on optimizing the working conditions and structure of direct contact heat transfer in order to improve heat transfer efficiency. …”
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Enhancing Security in CPS Industry 5.0 using Lightweight MobileNetV3 with Adaptive Optimization Technique by Mohammed A. Aleisa

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Research on the Thrust Allocation Method for Straight-Line Sailing of Multiple AUVs in Tandem Connection by Jin Zhang, Shengfan Zhu, Shuai Kang

“…Second, an improved Genetic Algorithm (GA) was developed to optimize thrust values for each unit in smaller configurations. …”
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Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…This decreases the complexity of the model without losing essential information. Finally, a Graph Convolutional Split-Attention Network (SGCSAN) for promisingly predicting whether the stock prices are going to hit the ground and fly high again or is going to nosedive with Humboldt Squid Optimization Algorithm (HSOA) is introduced to further improve accuracy with lesser error generation. …”
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A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

“…Therefore, in this study, we propose the YOLOV5M-SBSD tea bud lightweight detection model to address the above issues. The Fuding white tea bud image dataset was established by collecting Fuding white tea images; then the lightweight network ShuffleNetV2 was used to replace the YOLOV5 backbone network; the up-sampling algorithm of YOLOV5 was optimized by using CARAFE modular structure, which increases the sensory field of the network while maintaining the lightweight; then BiFPN was used to achieve more efficient multi-scale feature fusion; and the introduction of the parameter-free attention SimAm to enhance the feature extraction ability of the model while not adding extra computation. …”
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Using Cuckoo Search Algorithm to Predict Corporate Financial Risks and Alleviate Economic Uncertainty by Muqiao Cai

“…Advanced forecasting models must be combined with robust optimization methods to address these challenges effectively. …”
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A novel integrated TDLAVOA-XGBoost model for tool wear prediction in lathe and milling operations by Zhongyuan Che, Chong Peng, Chi Wang, Jikun Wang

“…However, their effectiveness is highly dependent on hyperparameters, and empirical identification of optimal configurations remains challenging. This study proposes an integrated model for tool wear prediction in CNC machining that combines improved algorithms with XGBoost. …”
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Leveraging IGOOSE-XGBoost for the Early Detection of Subclinical Mastitis in Dairy Cows by Rui Guo, Yongqiang Dai

“…Subclinical mastitis in dairy cows poses a significant challenge to the dairy industry, leading to reduced milk yield, altered milk composition, compromised animal health, and substantial economic losses for dairy farmers. A model based on the XGBoost algorithm, optimized with an Improved GOOSE Optimization Algorithm (IGOOSE), is presented in this work as an innovative approach for predicting subclinical mastitis in order to overcome these problems. …”
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An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus by Di-Wen Kang, Shao-Qiang Ye, Sharifah Zarith Rahmah Syed Ahmad, Li-Ping Mo, Feng Qin, Pan Zhou

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Influence of Modal Decomposition Algorithms on Nonlinear Time Series Machine Learning Prediction Models in Engineering: A Case Study of Subway Tunnel Settlement by Qingmeng Shen, Yuming Wu, Limin Wan, Qian Chen, Yue Li, Zichao Liao, Wenbo Wang, Feng Li, Tao Li, Jiajun Shu

“…The results show that the prediction model with the integrated decomposition algorithm reduces the RMSE and MAE by 33% and 37%, respectively, which significantly improves the prediction accuracy and generalization ability of the neural network to meet the demand of practical engineering prediction and simultaneously enhances the risk warning ability of the model.…”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Basma Jumaa Saleh, Zaid Omar, Muhammad Amir As’ari, Vikrant Bhateja, Lila Iznita Izhar

“…While the baseline model achieves 88% accuracy on Data1 and 97.6% on Data2, the proposed ALS-IOAP-DNN4 model attains perfect accuracy (100%) on both datasets, demonstrating the effectiveness of ALS and advanced optimization techniques. …”
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