Flexible Demand Side Management in Smart Cities: Integrating Diverse User Profiles and Multiple Objectives by Nuno Souza e Silva, Paulo Ferrão

“…The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. …”
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Human Activity Recognition Using Graph Structures and Deep Neural Networks by Abed Al Raoof K. Bsoul

“…To address this, we applied the Firefly Optimization Algorithm to fine-tune the hyperparameters of both the graph-based model and a CNN baseline for comparison. …”
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Advancing Pile-Bearing Capacity Prediction with Meta-Heuristic Enhanced Specific ANFIS strategys by Zhongmiao Dang

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A Robust Multi-Objective Evolutionary Framework for Artificial Island Construction Scheduling Under Dynamic Constraints by Tianju Zheng, Liping Sun, Mingwei Li, Guangyao Yuan, Shuqi Li

“…To effectively address the complexities of this model, we develop and employ the Multi-Objective Adaptive Cooperative Evolutionary Marine Genetic Algorithm (MACEMGA). MACEMGA combines cooperative coevolution, adaptive dynamic weighting, dynamic penalty functions, and advanced genetic operators to navigate the solution space efficiently and identify Pareto optimal schedules. …”
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A Comprehensive System to Support Decision Making in Highly Complex Project Portfolio Situations by Efrain Solares, Eduardo Fernandez, Carlos A. Coello Coello, Xochitl Segura Lozano, Reimundo Moreno-Cepeda, Raymundo Diaz

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Fleet Size and Mix Vehicle Routing Problem (FSMVRP), Adapted Large Neighbourhood Search Heuristic Optimization ProposalWith a Plant-capacity and Multi-day Planning Algorithm: A Liv... by Alperen Ekrem Çelikdin

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Reducing PAPR in NOMA Waveforms Using Genetic-Enhanced PTS and SLM: A Low-Complexity Approach for Improved throughput, power spectral density, and Power Efficiency by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…Current hybrid solutions, such as Genetic Algorithm (GA)-based optimization, provide better performance but are still computationally intensive. …”
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A Bat Algorithm with Mutation for UCAV Path Planning by Gaige Wang, Lihong Guo, Hong Duan, Luo Liu, Heqi Wang

“…Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. …”
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Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
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Size optimization method of the Watt-II six-bar mechanism based on particle swarm optimization by H. Ye, H. Ye, Z. Niu, Z. Niu, D. Han, D. Han, X. Su, X. Su, W. Chen, W. Chen, G. Tu, G. Tu, T. Zhu, T. Zhu

“…The results show that the optimized mechanism can improve the output capacity of the mechanism and reduce the force of the parts while ensuring the motion stability, which has certain practical significance in engineering.…”
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Hardware implementation of RSA encryption algorithm based on pipeline by Yang Longfei, Lu Shi, Peng Kuang

“…Experimental results on a Xilinx XC7K410T FPGA development board demonstrate that while maintaining encryption speed, the hardware resources used by the improved RSA encryption algorithm are only half of those of the previous parallel structure and can operate at higher frequencies.…”
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FM‐YOLOv8:Lightweight gesture recognition algorithm by Fanghai Li, Xitai Na, Jinshuo Shi, Qingbin Sun

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Provident garbage collection algorithm for SSD storage system by Xuezhen TU, Zhenjiang Huang, Zhengguang CHEN

“…A predictive based proactive garbage collection algorithm was proposed.Firstly,the data was separated according to different heat factors,then the upper and lower predictions were performed on the number of different types of page allocation requests (PAR) that would be reached in the future.While satisfying the page allocation request lower prediction,the PAR upper prediction requirement was maximally satisfied,the WA problem was optimized,and invalid effective data migration was reduced,thereby maximizing the garbage collection utility.A mathematical model was defined for this problem,and an algorithm for obtaining the approximate optimal solution was given.The applicable scenario of the model was analyzed.The practical results show that the algorithm can obtain the maximum benefit and can significantly improve the performance of SSD and reduce the cost.…”
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Information entropy based match field cutting algorithm by Peng-hao SUN, Ju-long LAN, Shao-jun ZHANG, Jun-fei LI

“…With the increasing diversity of network functions,packet classification had a higher demand on the number of match fields and depth of match table,which placed a severe burden on the storage capacity of hardware.To ensure the efficiency of matching process while at the same time improve the usage of storage devices,an information entropy based cutting algorithm on match fields was proposed.By the analysis on the redundancy of match fields and distribution pattern in a rule set,a match field cutting model was proposed.With the mapping of matching process to the process of entropy reduction,the complexity of optimal match field cutting was reduced from NP-hard to linear complexity.Experiment results show that compared to existing schemes,this scheme can need 40% less TCAM storage space,and on the other side,with the growing of table size,the time complexity of this algorithm is also far less than other algorithms.…”
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An intelligent hybrid grey wolf-particle swarm optimizer for optimization in complex engineering design problem by Muhammad Suhail Shaikh, Haoyue Lin, Senlin Xie, Xiaoqing Dong, Yifan Lin, Chandan Kumar Shiva, Wulfran Fendzi Mbasso

“…In Case 1, the improvement is 71.61%, while in Cases 2 and 4 obtained a 99% improvement. …”
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Multi-Level Particle System Modeling Algorithm with WRF by Julong Chen, Bin Wang, Rundong Gan, Xuepeng Mou, Shiping Yang, Ling Tan

“…Based on the multi-scale mean-shift clustering algorithm, Adaptive Kernel Density Estimation (AKDE) is introduced to map density to bandwidth, achieving adaptive adjustment of clustering bandwidth while reducing computational resources and improving cloud hierarchy. …”
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The P Balasubramaniam Award-2024 Singapore Orthopaedic Association Annual Scientific Meeting Award: Novel artificial intelligence algorithm for soft tissue balancing and bone cuts... by Matthew Song Peng Ng, Ryan Wai Keong Loke, Melvin Kian Loong Tan, Yau Hong Ng, Zi Qiang Glen Liau

“…Conclusion Our novel AI algorithm significantly improves accuracy in achieving surgeon-defined target extension and flexion gaps while reducing soft tissue balancing and total surgical duration. …”
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A Vehicle Path Planning Algorithm: QDDG-RRT by Ruixin Zhang, Qing Xu, Kai Sun, Yi Liu, Ximming Zhu, Guo Zhang, Xiang Cheng

“…The Rapidly-exploring Random Tree (RRT) algorithm, while widely used, suffers from slow search speeds, numerous inflection points, and redundant operations. …”
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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…Thus, this study has developed a novel feature-based enhanced boosting algorithm (F-EBA). The proposed model covers two pipelines, the feature engineering pipeline which improves the quality of features by picking up the most relevant features while the classification pipeline uses an ensemble approach designed to boost/elevate the model’s performances. …”
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Feature engineering through two-level genetic algorithm by Aditi Gulati, Armin Felahatpisheh, Camilo E. Valderrama

“…We evaluated our approach on twelve datasets from various fields, achieving an average F1 score improvement of 1.5% while reducing the feature set size by 54.5%. …”
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