Active and Reactive Power Control for Wind Turbines Based DFIG Using LQR Controller with Optimal Gain-Scheduling by Ashraf Radaideh, Mu’men Bodoor, Ayman Al-Quraan

“…Active and reactive power decoupling is performed using the field-oriented vector control which is used to simplify DFIG’s nonlinearity and derive a compact linearized state-space model. The performance of the optimal controller represented by a linear quadratic regulator is further enhanced using the whale optimization algorithm in a multiobjective optimization environment. …”
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Physics-Informed Neural Network for Load Margin Assessment of Power Systems with Optimal Phasor Measurement Unit Placement by Murilo Eduardo Casteroba Bento

“…The proposed optimization model will also determine an optimal location of Phasor Measurement Units (PMUs) at system buses whose measurements will be inputs to the PINN. …”
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Optimal path selection and secured data transmission in underwater acoustic sensor networks: LSTM-based energy prediction. by Sathish Kaveripakam, Ravikumar Chinthaginjala

“…Further, the data is transmitted via the optimal path securely by encrypting the data with the proposed improved blowfish algorithm (IBFA). …”
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Optimizing Energy Efficiency in Vehicular Edge-Cloud Networks Through Deep Reinforcement Learning-Based Computation Offloading by Ibrahim A. Elgendy, Ammar Muthanna, Abdullah Alshahrani, Dina S. M. Hassan, Reem Alkanhel, Mohamed Elkawkagy

“…Given the complexity of this problem in large-scale vehicular networks, the study formulates an equivalent reinforcement learning model and employs a deep learning algorithm to derive optimal solutions. …”
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Exploration on the Optimal Application of Mobile Cloud Computing in Enterprise Financial Management under 5G Network Architecture by Yanlin Guo, Huwei Li

“…In order to improve the effect of modern enterprise financial management, this paper improves the mobile cloud computing resource scheduling algorithm under the 5G network architecture. …”
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System identification and robust PID controller tuning of quarter car suspension system using hybrid optimization techniques by S. Sakthiya Ram, C. Kumar, R. Saravanakumar, David Banjerdpongchai

“…After validating the resulting dynamic model, various PID controllers are designed using standard metaheuristic algorithms—Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA). …”
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Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction by Bokun Ning, Fang Zhao, Haiyong Luo, Dan Luo, Wenhua Shao

“…Frequent cycle slips in carrier phase measurements and ambiguity resolution algorithms increase computational burden without improving positioning accuracy. …”
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Research on Capacity Optimization Configuration of Wind-solar-storage-load Micro-grid System Based on Energy Router by ZHANG Jietian, LI Chi

“…Based on the above micro-grid system model, the optimal energy storage configuration of wind power system and solar power system and system is realized by simulated annealing algorithm, and the accuracy and effectiveness of the proposed are verified by a case study. …”
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Optimal Planning of Terminal Locations and Capacity of UHVDC Considering Constraints of Receiving-End Power Grid Support Capability by Linlin YU, Ge YAN, Xintong YAN, Yubin MAO, Shuyu CHEN, Tiantian LI, Yunfeng WEN

“…Furthermore, the model is decomposed into a upper layer for planning and a lower layer for operation checking, and the the Benders decomposition algorithm is used to realized the iterative solution of the complex optimization model. …”
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Incorporating soil moisture data into a machine learning framework improved the predictive accuracy of corn yields in the U.S. by Bishwoyog Bhattarai, Zachary Leasor, André Fróes de Borja Reis

“…Leveraging machine learning (ML) techniques capable of handling large-scale datasets offers a promising alternative for uncovering hidden patterns and generating actionable insights to improve crop yield. We hypothesize that incorporating soil moisture and temperature data from land surface models into a ML framework will enhance accuracy of corn yield predictions. …”
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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

“…This approach resulted in two distinct optimized models: a resource-efficient variant that reduced resource consumption by 12% with only a 0.2% decrease in RMS micro-benchmark IPC, and a performance-optimized model that improved performance by 29.5% while increasing resource usage by just 4.20%. …”
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Research on Long-Term Scheduling Optimization of Water–Wind–Solar Multi-Energy Complementary System Based on DDPG by Zixing Wan, Wenwu Li, Mu He, Taotao Zhang, Shengzhe Chen, Weiwei Guan, Xiaojun Hua, Shang Zheng

“…To address the challenges of high complexity in modeling the correlation of multi-dimensional stochastic variables and the difficulty of solving long-term scheduling models in continuous action spaces in multi-energy complementary systems, this paper proposes a long-term optimization scheduling method based on Deep Deterministic Policy Gradient (DDPG). …”
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Optimizing Energy Efficiency in Cloud Data Centers: A Reinforcement Learning-Based Virtual Machine Placement Strategy by Abdelhadi Amahrouch, Youssef Saadi, Said El Kafhali

“…To address this issue, we propose a novel energy-efficient virtual machine (VM) placement strategy that integrates reinforcement learning (Q-learning), a Firefly optimization algorithm, and a VM sensitivity classification model based on random forest and self-organizing map. …”
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Decoding On-Field Roles in Football: A Sociological Analysis Using Intelligent MCDM Algorithm With Fuzzy Information for Player Positioning and Technical-Tactical Behavior by Lu Yan, Nannan Wang, Rui Chen

“…So, football strategy demands a decision-making model that considers these details and assists in achieving optimal team performance. …”
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Optimizing Location of Car-Sharing Stations Based on Potential Travel Demand and Present Operation Characteristics: The Case of Chengdu by Yu Cheng, Xu Chen, Xiaohua Ding, Linting Zeng

“…This study aims to use different data source with statistical models and machine learning algorithm to help car-sharing operator to choose the optimal location of new stations and adjust the location of existing stations. …”
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Multi-scenario Dynamic Simulation and Optimization of Urban Ventilation Environment: A Case Study of Taiyuan Metropolitan Area by Junda HUANG, Yuncai WANG

“…Then, a prediction model is constructed based on the random forest algorithm. …”
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An Efficient Mutual Authentication and Fractional Lyrebird Optimization With Deep Learning–Based SIP-Based DRDoS Attack Detection by V. Sreenivasulu, C. V. Ravikumar

“…In this article, a deep learning model fractional lyrebird optimization algorithm–deep stack autoencoder (FLOA-DSA) is developed for the detection of SIP-based distributed reflection denial-of-service (DRDoS) attacks in SIP network. …”
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Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…While, AFT measured by ultrasound improved the predictive ability of all the models (R² of KNN showed highest increase of 12.35 %). …”
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The Optimal Dispatch for a Flexible Distribution Network Equipped with Mobile Energy Storage Systems and Soft Open Points by Yu Ji, Ying Zhang, Lei Chen, Juan Zuo, Wenbo Wang, Chongxin Xu

“…In this paper, a case study uses a regional road network in Chengdu coupled with an IEEE 33-node standard grid, and the model is solved using the non-dominated sorting genetic algorithm III (NSGA-III) algorithm. …”
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Collaborative Optimization of Passenger Control Strategy and Train Operation Plan with Variable Formations for a Rail Transit Network by Yonghao Yin, Jun Chen, Wenrui Zhao

“…We proposed a passenger control strategy and train operation plan collaborative optimization (PCS&TOP) model to schedule the train operation that improves the efficiency of passengers’ travel and reduces the cost of train operation for a rail transit network. …”
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