An Improved Autonomous Emergency Braking Algorithm for AGVs: Enhancing Operational Smoothness Through Multi-Stage Deceleration by Wenbo Li, Junting Qiu

“…The AEB algorithm not only considers straight-line driving scenarios but also optimizes deceleration strategies for turning scenarios, adjusting the deceleration detection range according to the turning trajectory. …”
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Research on Optimum Design of Waste Recycling Network for Agricultural Production by Huabin Wu, Jing Zhang, Yanshu Ji, Yuelong Su, Shumiao Shu

“…This study not only improved the recycling efficiency of APW but also effectively reduced the recycling costs of APW.…”
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Heart Disease Prediction Using a Hybrid Feature Selection and Ensemble Learning Approach by Isha Gupta, Anu Bajaj, Manav Malhotra, Vikas Sharma, Ajith Abraham

“…This approach also integrated GA for hyperparameter tuning, enhancing predictive accuracy. …”
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Implementation of Fisher-Yates Shuffle and Fuzzy Tsukamoto in Nusantara Educational Game by Khairul Insan Karim, Chairunnisa Lamasitudju, Ryfial Azhar, Fizar Syafaat, Anisa Yulandari

“…The One Group Pretest- Posttest Design method was also applied. The findings show that the Fisher-Yates Shuffle enhances challenge and engagement, while the Fuzzy Tsukamoto algorithm ensures balanced scoring, fostering motivation. …”
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A New Model for Enhancing Efficiency in On-Chip Optical ‎Networks Based on Adaptive Routing Algorithm.‎ by Mohammadreza Hemmati, Sayed Mohammad Ali Zanjani, Elham Yaghoubi

“…Therefore, providing an error-tolerant routing algorithm plays a crucial role in the development of on-chip network architecture. …”
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Legendre based neural networks integrated with heuristic algorithms for the analysis of Lorenz chaotic model: an intelligent and comparative study by Khalid Masood, Muhammad Arshad, Muhammad Abubakar, Muhammad Naeem Aslam, Mohammed A. Alghamdi, Sultan H. Almotiri

“…The hybrid FA-AOA optimization is also investigated to verify the LENN model accuracy and reliability. …”
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Research on intra-day multi-objective operation control of distribution network system under quantum communication optimization by QIAN Hao, DONG Zhihui, XIANG Jundong, ZHENG Jiewen, TANG Zhipeng, GUO Qiang

“…In order to solve this multi-objective collaborative optimization model, the imperial competition algorithm is combined with genetic algorithm, and the concept of quantum state probability is introduced. …”
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A systematic review of reinforcement learning-based control for microgrids: trends, challenges, and emerging algorithms by A. V. Waghmare, V. P. Singh, T. Varshney, P. Sanjeevikumar

“…A comparative analysis based on performance of RL algorithms, and RL based control with other types of control frameworks is also systematically presented. …”
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Shear Strength Determination in RC Beams Using ANN Trained with Tabu Search Training Algorithm by Alireza Shahbazian, Hamidreza Rabiefar, Babak Aminnejad

“…To assess its feasibility, the ANNs were also modeled using the Particle Swarm Optimization, and Imperialist Competitive Algorithms. …”
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Computational Algorithms for Representing Aircraft Instruments with Barometric Physics (Numerical Methods Applied to Flight Simulation) by Adan Ramirez-Lopez

“…The algorithms developed for this purpose also include the corresponding relationship between the physical variables, such as the speed and displacement, and the standard atmosphere to provide an equivalent value. …”
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Optimization of rectangular micro-channel heat exchangers for use in HCPV panels through genetic algorithm by Pedro D. Pontes, Luz Elena P. Chenche, João A. Lima, Carolina P. Naveira-Cotta, Ana S. Moita

“…In addition to the thermal parameters, the pressure drop inside the micro-heat exchanger is also considered in the optimization process. Although only single-phase flows are handled now, the algorithm can be extended to other flow regimes. …”
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Low-complexity likelihood probability derivation algorithm for non-binary LDPC-coded modulation system by Guang-hua HE, Bao-ming BAI, Xiao MA, Bing LI

“…The derivation of likelihood probabilities which are sent into the decoder in many LDPC-coded modulation systems is a challenging task especially when high-order modulations are used.This is because likelihood probabilities are usually complicated functions of the channel output and their calculation also requires knowledge of the channel parameters.To this end,a low-complexity likelihood probability derivation algorithm was proposed.Also,the Euclidean distance between the received signal and the constellation points was considered to divide the constellation points into two signal sets.Simulation results show that the proposed algorithm provides good trade-offs between performance and complexity,making it a good candidate for the hardware implementation of the front-end in the non-binary LDPC decoders.…”
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RESEARCH ON PERFORMANCE PREDICTION OF THIN SEAM SHEARER BY COMBINING GENETIC ALGORITHM WITH BP NEURAL NETWORK by ZHAO LiJuan, JIN ZhongFeng

“…The result shows that method not only speeding up the convergence speed but also improve the training accuracy,also obviously valuable for the performance prediction of thin seam shearer.…”
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Optimization of SVM Parameters with Hybrid CS-PSO Algorithms for Parkinson’s Disease in LabVIEW Environment by Duygu Kaya

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VERIFICATION OF THE PARSEC METHOD AND OPTIMIZATION OF NACA-4412, SG-6043 USING GENETIC ALGORITHM IN MATLAB by Raheem Alhamdawee, M. Manzoor Hussain

“…For instance lift coefficient (CL), drag coefficient (CD), and the ratio CL/Cd at different angles of attack. The study also includes the improvement of the aerodynamic design of both airfoils through the use of a genetic algorithm which is coded and run in MATLAB, with the PARSEC parameters used as the base for optimization. …”
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Back analysis of geomechanical parameters based on a data augmentation algorithm and machine learning technique by Hui Li, Weizhong Chen, Xianjun Tan

“…Furthermore, the superiority of the OPSO-SVM algorithm is also demonstrated by comparing the displacement prediction capability of various algorithms through four indices. …”
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Study of Impact of Moment Information in Demand Forecasting on Distributionally Robust Fulfillment Rate Improvement Algorithm by Haodong Feng

“…Once the regional distribution center is also out of stock, a lost sale occurs. This paper improves a distributionally robust allocation model aimed at enhancing the fulfillment rates of front distribution centers while also preserving the overall fulfillment rate within the region. …”
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5G network slicing function migration mechanism based on particle swarm optimization algorithm by Qiang CHEN, Caixia LIU, Lingshu LI

“…In multi-application scenarios of 5G,data traffic often increases dramatically.Virtual machine resources in network slicing may not meet the normal needs of users.In view of this,a network slicing function migration mechanism aiming at load balancing was proposed.The mechanism simulates the virtual machine into particles based on particle swarm optimization algorithm.In the process of migration,all particles were divided into several subgroups,and particle swarm optimization algorithm was applied within and among groups.According to the historical optimal solution and the current global optimal solution,the particle location was updated,and the best target particles were determined by selecting the smaller particle size of the particle in real time.The mechanism not only improves the convergence speed,but also improves the accuracy of the algorithm.Compared with other migration methods,the results show that the proposed migration mechanism has the advantages of high accuracy and fast convergence.And it can also improve the efficiency of resource utilization,reduce the energy consumption of data center,and has better adaptability.…”
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A Two-Stage Bin Packing Algorithm for Minimizing Machines and Operators in Cyclic Production Systems by Yossi Hadad, Baruch Keren

“…Our algorithm treats the problem of minimum machines as a bin packing problem (BPP), and the problem of determining the number of operators required is also modeled as the BPP, but with constraints. …”
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Hybrid genetic algorithms: solutions in realistic dynamic and setup dependent job-shop scheduling problems by Rogério M. Branco, Antônio S. Coelho, Sérgio F. Mayerle

“…The proposed genetic algorithm executes two important functions: choose the routes using dispatching rules when forming each individual from a defined set of available machines and, also make the scheduling for each of these individuals created. …”
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