Finite Mixture Model-Based Analysis of Yarn Quality Parameters by Esra Karakaş, Melik Koyuncu, Mülayim Öngün Ükelge

“…Model parameters are estimated using the expectation–maximization (EM) algorithm, and model selection is guided by the Akaike and Bayesian information criteria (AIC and BIC). …”
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LHS-GA Based H-Infinity Control for Robust Airfoil Flutter Suppression by Malek Rekik, Omar Khaled, Karolos Grigoriadis, Matthew A. Franchek

“…The objective is to design a robust controller that effectively suppresses flutter while optimizing performance metrics, specifically time-domain constraints and settling time. …”
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Architectural Exploration and Performance Enhancement of the CVA6 RISC-V Core Using the Gem5 Simulation Framework by Umer Shahid, Muhammad Tahir, Bilal Zafar, Ayesha Ahmad, Shanzay Wasim, Bisal Saeed

“…To further enhance the architecture, we integrated machine learning algorithms to optimize performance and resource efficiency. …”
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A Neural Network-Based Structural Parameter Assessment Method for Prefabricated Concrete Pavement by Yongsheng Tang, Yunzhen Lin, Tao Yu

“…Therefore, a new method based on a neural network is applied to implement a long-term structural assessment, with the input being monitored strain data; it is named the jellyfish search algorithm-optimized BP neural network (JS-BP) model. …”
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Water quality index modelling and its application on artificial intelligence (AI) in conjunction with machine learning (ML) methodologies for mapping surface water potential zones... by Abhijeet Das

“…., World Health Organization guidelines is implanted to decipher the values ranging from natural to anthropogenic contribution.In the Mahanadi River Basin, Odisha, however, this study has highlighted the evaluation of surface water quality (WQ) for drinking reasons by the combined use of Machine Learning (ML) methodologies like Genetic Algorithm Particle Swarm Optimization-based WQI (GAPSO-WQI), with dependability-oriented decision-making approaches such as Firefly Algorithm (FA) and Algorithm of Weeds (AW), that have been used for river water quality monitoring and assessment due to their dependability and feasibility. …”
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Path Planning for Rapid DEDAM Processing Subject to Interpass Temperature Constraints by Glenn W. Hatala, Edward W. Reutzel, Qian Wang

“…To evaluate this, a compact analytic thermal model is used to predict the thermal history during laser-based directed energy deposition (DED-LB/M) hot wire (lateral feeding) of ER100S-G, a welding wire equivalent to high yield steel. A greedy algorithm, integrated with the thermal model, identifies a tool path order that ensures compliance with the interpass requirement of the material while minimizing interpass dwell time and, thus, the total deposition time. …”
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Extraction and analysis of aerosol anomalies associated with multiple shallow earthquakes based on MODIS AOD products by Ping Lu, Xiao Gao, Zhixuan Xiong, Yu Shang

“…The results suggest that a 1° buffer is the optimal spatial window for most earthquake cases. …”
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A Blockchain Network Communication Architecture Based on Information-Centric Networking by Yufei Zhou, Rui Han, Yang Li

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Optimizing winner determination for sustainability and timeliness in fresh agricultural product logistics service procurement auctions: insights from a fourth-party logistics persp... by Yi Zhou, Mingqiang Yin, Qiang Liu, Xiaohu Qian, Delong Jin, Xianming Lang

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Blockchain-Based UAV-Assisted Mobile Edge Computing for Dual Game Resource Allocation by Shanchen Pang, Yu Tang, Xue Zhai, Siyuan Tong, Zhenghao Wan

“…This paper proposes a two-stage optimization (DSO) algorithm for UAV-assisted MEC, combining Stackelberg game theory and auction mechanisms to optimize resource allocation among servers, UAVs, and users. …”
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Spectrum Efficient Mode Selection and Resource Allocation Optimization for D2D Communication in HetNet: A Multi-Agent Q-Learning Approach by Ali Majid Hasan Alibraheemi, Mhd Nour Hindia, Tengku Faiz Tengku Mohmed Noor Izam, Kaharudin Dimyati

“…Then, based on the allocated optimal channel, a modified MAQL algorithm is introduced to allocate the optimal power for each D2D transmitter. …”
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Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

“…GA handles feature selection, while PSO optimizes MLP hyperparameters (e.g., learning rate, neurons, activation functions). …”
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Multi-Objective Optimization of Pressure-Reducing Valves Operation in Extreme Water Consumption Scenarios (Case Study: Najaf Abad Urban Water Distribution Network) by Seyed Pedram Jazayeri Farsani, Ramtin Moeini

“…Additionally, three objective functions were optimized using the NSGA-II multi-objective optimization algorithm. …”
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Power-Efficient UAV Positioning and Resource Allocation in UAV-Assisted Wireless Networks for Video Streaming with Fairness Consideration by Zaheer Ahmed, Ayaz Ahmad, Muhammad Altaf, Mohammed Ahmed Hassan

“…The aim of this research is to maximize the overall users’ quality of experience in terms of power-efficient adaptive video streaming by fair distribution and smooth transition of video rates. The joint optimization includes power minimization, efficient resource allocation, i.e., transmit power and bandwidth, and efficient two-dimensional positioning of the UAV while meeting system constraints. …”
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Frequency regulation of PV-reheat thermal power system via a novel hybrid educational competition optimizer with pattern search and cascaded PDN-PI controller by Serdar Ekinci, Davut Izci, Ozay Can, Mohit Bajaj, Vojtech Blazek

“…The hECO-PS tuned PDN-PI controller achieved a minimum integral of time-weighted absolute error (ITAE) value of 0.4464, outperforming conventional methods like the modified whale optimization algorithm and sea horse algorithm, which yielded ITAE values of 2.6198 and 0.8598, respectively. …”
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Design of an intelligent optimization system for high-altitude photovoltaic power plant output power prediction and enhancement using GVSAO-CNN-BiGRU-Attention by Shuai Yuan, Hui Zhou, Kai Zhao

“…The system integrates convolutional neural networks (CNN), bi-directional gated recurrent units (BiGRU), attention mechanisms, and genetic algorithm optimization (GVSAO). The CNN extracts spatial features, while the BiGRU enhances temporal dependency modeling, effectively capturing short- and long-term patterns. …”
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Passenger Flow Prediction for Rail Transit Stations Based on an Improved SSA-LSTM Model by Xing Zhao, Chenxi Li, Xueting Zou, Xiwang Du, Ahmed Ismail

“…According to the experimental results, the proposed SSA-LSTM model has a more effective performance than the Support Vector Regression (SVR) method, the eXtreme Gradient Boosting (XGBoost) model, the traditional LSTM model, and the improved LSTM model with the Whale Optimization Algorithm (WOA-LSTM) in the passenger flow prediction. …”
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A Dynamic Analysis of a Cantilever Piezoelectric Vibration Energy Harvester with Maximized Electric Polarization Due to the Optimal Shape of the Thickness for First Eigen Frequency by Paulius Skėrys, Rimvydas Gaidys

“…This study presents an analytical and experimental approach to enhance cantilever-based piezoelectric energy harvesters by optimizing thickness distribution. Using a gradient projection algorithm within a state-space framework, the unimorph beam’s geometry is tailored while constraining the first natural frequency. …”
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IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration by Sami Binyamin, Sami Ben Slama

“…The proposed approach can dynamically optimize household energy flows, deploying real-time data and adaptive algorithms to balance energy demand and supply. …”
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Optimizing Virtual Power Plant Operations in Energy and Frequency Regulation Reserve Markets: A Risk-Averse Two-Stage Scenario-Oriented Stochastic Approach by Asad Mujeeb, Zechun Hu, Jianxiao Wang, Rui Diao, Likai Liu, Zhiyuan Bao

“…Furthermore, the numerical findings compare the risk-neutral VPP framework with the proposed risk-sensitive VPP strategy, revealing a trade-off between expected profit and CvaR, indicating that as the risk aversion parameter escalates, expected profits decline while CVaR value rises, underscoring the importance of risk management in VPP optimization.…”
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