New chemometrics-assisted spectrophotometric methods for simultaneous determination of co-formulated drugs montelukast, rupatadine, and desloratadine in their different dosage comb... by Marco M. Z. Sharkawi, Nehal F. Farid, Moataz H. Hassan, Said A. Hassan

“…The proposed approaches, partial least squares-1 (PLS-1) and artificial neural network (ANN), were optimized using genetic algorithm (GA) to select the most influential wavelengths, enhancing model performance. …”
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The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis by Zeyu Chen, Zheng Lin, Zihan Lin, Qi Zhang, Haoyun Zhang, Haiwen Li, Qing Chang, Jianqi Sun, Feng Li

“…The potential improvements of AI in CT assessments, including time-series CT analysis, optimization of AI algorithms, utilization of multi-modal data, and discovery of new biomarkers through unsupervised algorithms, could be introduced to make a more accurate and convenient assessment for the prognosis of IPF patients. …”
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From Pairwise Comparisons of Complex Behavior to an Overall Performance Rank: A Novel Alloy Design Strategy by Rafael Herschberg, Lisa Rateau, Laure Martinelli, Fanny Balbaud-Célérier, Jean Dhers, Anna Fraczkiewicz, Gérard Ramstein, Franck Tancret

“…In this case, the method is applied to the design of wear-resistant hard-facing alloys by also associating it with a combinatorial optimization of their composition by a multi-objective genetic algorithm. …”
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Efficient distributed model sharing strategy for data privacy protection in Internet of vehicles by Zijia MO, Zhipeng GAO, Yang YANG, Yijing LIN, Shan SUN, Chen ZHAO

“…Aiming at the efficiency problem of privacy data sharing in the Internet of vehicles (IoV), an efficient distributed model sharing strategy based on blockchain was proposed.In response to the data sharing requirements among multiple entities and roles in the IoV, a master-slave chain architecture was built between vehicles, roadside units, and base stations to achieve secure sharing of distributed models.An asynchronous federated learning algorithm based on motivate mechanism was proposed to encourage vehicles and roadside units to participate in the optimization process.An improved DPoS consensus algorithm with hybrid PBFT was constructed to reduce communication costs and improve consensus efficiency.Experimental analysis shows that the proposed mechanism can improve the efficiency of data sharing and has certain scalability.…”
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An Empirical Taxonomy of Video Summarization Model From a Statistical Perspective by Sai Babu Veesam, Aravapalli Rama Satish

“…Some of the notable techniques include the SVS_MCO method using DBSCAN clustering optimized by the Artificial Algae Algorithm and the KDAN framework, which leverages knowledge distillation for supervised summarization. …”
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Multi-resource joint management strategy for 5 G network slicing based on POMDP by Yale Li

“…Such processes are capable of perceiving changes in network topology and dynamically adjusting resource allocation to adapt to constantly changing network conditions. Furthermore, the model employs a hybrid heuristic value iterative algorithm to optimize computational efficiency, reduce network latency, improve throughput, and enhance resource utilization. …”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…AI-enabled linguistics modeling promotes scalable optimization and context-aware applications of financial analytics, and realizes cost transparency improvements in automated investment systems. …”
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A Machine Learning-Based Parameterized Tropical Cyclone Precipitation Model by Yi Lu, Jie Yin, Peiyan Chen, Hui Yu, Sirong Huang

“…Taking Shanghai, a coastal megacity, as a study area and based on the observations from 192 meteorological stations in the city during 2005–2018, this study optimized the parameterized Tropical Cyclone Precipitation Model (TCPM) initially designed for TCs at the national scale (China) to the local or regional scales by using machine learning (ML) methods, including the random forest (RF), extreme gradient boosting (XGBoost), and ensemble learning (EL) algorithms. …”
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Collaborative multiview time series modeling for vehicle maintenance demand prediction by Fanghua Chen, Deguang Shang, Gang Zhou, Ke Ye, Fujie Ren, Guofang Wu

“…To enhance the interaction between distinct time points and temporal dependencies, we developed a dependency-aware learning algorithm that effectively integrates and weighs the information and dependencies at each time step, thereby improving the model’s ability to capture the complex relationships among maintenance projects over time. …”
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Adaptive sliding mode control based on maximum power point tracking for boost converter of photovoltaic system under reference voltage optimizer by Borhen Torchani, Ahmad Taher Azar, Ahmad Taher Azar, Ahmad Taher Azar, Anis Sellami, Saim Ahmed, Saim Ahmed, Ibrahim A. Hameed, Ibraheem Kasim Ibraheem, Moamin Ibrahim Jameel Al-Obaidi

“…A PI controller calculates the reference current based on this power. The APISMC control modeling utilizes all its reference variables to synthesize the sliding surface and duty cycle for optimal boost converter control. …”
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Effective Facial Expression Recognition System Using Artificial Intelligence Technique by Imad S. Yousif, Tarik A. Rashid, Ahmed S. Shamsaldin, Sabat A. Abdulhameed, Abdulhady Abas Abdullah

“…This paper presents an improved performance of the Facial Expression Recognition (FER) systems via augmentation in Artificial Neural Networks and Genetic Algorithms, two renowned artificial intelligence techniques possessing disparate strengths. …”
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Hybrid Machine Learning in Hydrological Runoff Forecasting: An Exploration of Extreme Gradient-Boosting and Categorical Gradient Boosting Optimization in the Russian River Basin by Reza Seifi Majdar, Ali Rahnamaei, Vahid Babazadeh

“…Recent advances in machine learning (ML) have opened new opportunities to improve prediction accuracy. This study focuses on evaluating commonly used ML methods for runoff prediction, with an emphasis on simplicity and comparability to more advanced models. …”
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A Behavioral Robotics Approach to Radiation Mapping Using Adaptive Sampling by Joel Adams, Brendon Cintas, Nakwon Sung, Anthony Abrahao, Leonel Lagos, Dwayne McDaniel

“…The results additionally demonstrate that dynamically adjusting the optimization algorithm’s exploration tendency based on the arm’s collision history improves the system’s ability to navigate cluttered environments and construct accurate radiation maps without getting stuck in unreachable areas.…”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…The fusion of Artificial intelligence (AI) with computational chemistry has revolutionized drug discovery by enhancing compound optimization, predictive analytics, and molecular modeling. …”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

“…The proposed strategy combines machine learning algorithms, including multilayer perceptron neural network (MLPNN), generalized additive model (GAM), Gaussian kernel regression (GKR), support vector machine (SVM), and Gaussian process regression (GPR) with artificial intelligence-based metaheuristic optimization algorithms (PSO and GA) to optimize their structural/training parameters. …”
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Privacy-Preserving Diabetes and Heart Disease Prediction via Federated Learning and WCO by Sachikanta Dash, Sasmita Padhy, Preetam Suman, Sandip Mal, Lokesh Malviya, Amrit Suman, Jaydeep Kishore

“…This study introduces the Federated Learning with Weighted Conglomeration Optimization (FLWCO) model as a solution to these challenges. …”
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Synergistic Integration of LQR Control and PSO Optimization for Advanced Active Suspension Systems Utilizing Electro-Hydraulic Actuators and Electro-Servo Valves by Trong Tu

“…This research remarks the fundamentals of the experimental validation and further refinement of these control algorithms to adapt to various driving conditions and vehicle models, ultimately aiming to transition these optimized controllers from theoretical frameworks to practical, real-world applications. …”
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Enhancing Precision in OLT Measurements and Improving Agreement in Surgical Decision-Making: A Comprehensive Evaluation Using WBCT and Distance Mapping for Preoperative Planning by Agustin Barbero MD, Ben Efrima MD, Jari Dahmen MD, Amit Benady MD PhD, Camilla Maccario MD, Cristian Indino MD, Gino M M.M.J. Kerkhoffs MD, PhD, Federico Giuseppe Usuelli MD

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Feasibility of machine learning–based modeling and prediction to assess osteosarcoma outcomes by Qinfei Zhao, Weiquan Hu, Yu Xia, Shengyun Dai, Xiangsheng Wu, Jing Chen, Xiaoying Yuan, Tianyu Zhong, Xuxiang Xi, Qi Wang

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Nondestructive detection and classification of impurities-containing seed cotton based on hyperspectral imaging and one-dimensional convolutional neural network by Yeqi Fei, Zhenye Li, Tingting Zhu, Zengtao Chen, Chao Ni

“…By applying hyperspectral imaging and a one-dimensional deep learning algorithm, we detect and classify impurities in seed cotton after harvest. …”
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