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  1. 1061

    Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attenti... by Santosh Prabhakar Agnihotri, Mandar Padmakar Joshi

    Published 2024-02-01
    “…Our research identifies a significant research gap in the efficiency of existing methods, emphasizing the need for improved control parameter optimization and system behavior prediction for cost reduction and enhanced efficiency. …”
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    Article
  2. 1062

    A new sliding mode control strategy to improve active power management in a laboratory scale microgrid by Oscar Gonzales-Zurita, Jean-Michel Clairand, Guillermo Escrivá-Escrivá

    Published 2025-04-01
    “…This study proposes a robust control solution based on the second-order sliding mode control (SMC-2) algorithm to overcome the mentioned challenges. This algorithm employed a non-conventional sliding surface to improve the microgrid’s capacities for energy management. …”
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    Article
  3. 1063

    Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

    Published 2025-01-01
    “…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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    Article
  4. 1064

    AI driven automation for enhancing sustainability efforts in CDP report analysis by Ramya Rangarajan, Tamilarasi Kathirvel Murugan, Logeswari Govindaraj, Venyaa Venkataraman, Krithik Shankar

    Published 2025-07-01
    “…The proposed system leverages publicly available Carbon Disclosure Project (CDP)-reported data to predict emissions and optimize resource allocation. The primary objective of this research is to develop a cost-effective, scalable solution that reduces emissions, improves operational efficiency, and ensures regulatory compliance within supply chains. …”
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    Article
  5. 1065

    Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling by He Wang, Weiquan Huang, Sindri Magnússon, Tony Lindgren, Chen Chen, Junyu Wu, Yanjie Song

    Published 2025-08-01
    “…The experimental results show that the algorithm excels at solving the MOAEOSSP, outperforming competing algorithms across several metrics and demonstrating its effectiveness for complex optimization problems.…”
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    Article
  6. 1066

    Improving forest above-ground biomass estimation using genetic-based feature selection from Sentinel-1 and Sentinel-2 data (case study of the Noor forest area in Iran) by Armin Moghimi, Ava Tavakoli Darestani, Nikrouz Mostofi, Mahdiyeh Fathi, Meisam Amani

    Published 2024-04-01
    “…In this study, we employed a Genetic Algorithm (GA) to estimate forest Above-Ground Biomass (AGB) by selecting the most applicable features from both Sentinel-2 optical and Sentinel-1 Synthetic Aperture Radar (SAR) images in the Noor forest. …”
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    Article
  7. 1067

    Advanced Queueing and Location-Allocation Strategies for Sustainable Food Supply Chain by Amirmohammad Paksaz, Hanieh Zareian Beinabadi, Babak Moradi, Mobina Mousapour Mamoudan, Amir Aghsami

    Published 2024-09-01
    “…In large-scale scenarios, GOA significantly reduced processing times, ranging from 20.45 to 64.78 s. The optimization of processing facility locations within the supply chain, based on this model, led to improved balance between cost (up to $74.2 million), environmental impact (122,112 hazardous units), and waiting time (down to 11.75 h). …”
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    Article
  8. 1068

    Shared energy storage planning based on the adjustable potential of data center based on visual IOT platform by Lei Su, Wanli Feng, Haoyu Ma, Mingjiang Wei, RuoShi Gu, Ziya Chen, Junda Qin

    Published 2025-08-01
    “…Within this framework, a room-level energy management model is designed, integrating adjustable potential for batch-computing workloads and air conditioning systems to optimize time-of-use power consumption. Based the two-stage stochastic optimization model, a improved L-shaped algorithm is proposed to solve the planning model effectively, reducing computational complexity through problem decomposition. …”
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    Article
  9. 1069

    Enhancing agricultural sustainability: Optimizing crop planting structures and spatial layouts within the water-land-energy-economy-environment-food nexus by Haowei Wu, Zhihui Li, Xiangzheng Deng, Zhe Zhao

    Published 2025-06-01
    “…In this framework, the NSGA-II algorithm was used to construct the multi-objective optimization model of crop planting structures with consideration of water and energy consumption, greenhouse gas (GHG) emissions, economic benefits, as well as food, land, and water security constraints, while the model for planting spatial layout optimization was established with consideration of crop suitability using the MaxEnt model and the improved Hungarian algorithm. …”
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    Article
  10. 1070

    Identification and Evaluation of Profitable Technical Trading Rules in the Cryptocurrency Market: A Mixed Method Approach by Milad Abbasi, Somayeh Al-sadat Mousavi, Abbasali Jafari Nodoushan

    Published 2024-09-01
    “…ObjectiveThe purpose of this paper is to identify the most effective technical indicators in the cryptocurrency market, as viewed by market experts, optimize their performance using optimization algorithms, and ultimately compare the performance of the selected trading rules against each other and the buy-and-hold strategy. …”
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    Article
  11. 1071

    Doubly Constrained Robust Blind Beamforming Algorithm by Xin Song, Jingguo Ren, Qiuming Li

    Published 2013-01-01
    “…In contrast to the linearly constrained LSCMA, the proposed algorithm provides better robustness against the signal steering vector mismatches, yields higher signal captive performance, improves greater array output SINR, and has a lower computational cost. …”
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    Article
  12. 1072
  13. 1073

    Improving machine learning detection of Alzheimer disease using enhanced manta ray gene selection of Alzheimer gene expression datasets by Zahraa Ahmed, Mesut Çevik

    Published 2025-08-01
    “…To alleviate such an effect, this study proposes a gene selection approach based on the parameter-free and large-scale manta ray foraging optimization algorithm. Given the dimensional disparities and statistical relationship distributions of the six investigated datasets, in addition to four evaluated machine learning classifiers; the proposed Sign Random Mutation and Best Rank enhancements that substantially improved MRFO’s exploration and exploitation contributed to efficient identification of relevant genes and to machine learning improved prediction accuracy.…”
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    Article
  14. 1074

    Developing and Implementing an Artificial Intelligence (AI)-Driven System For Electricity Theft Detection by Nwamaka Georgenia Ezeji, Kingsley Ifeanyi Chibueze, Nnenna Harmony Nwobodo-Nzeribe

    Published 2024-09-01
    “…To achieve this, a Particle Swarm Optimization Algorithm (PSO) was applied to improve training performance of the SVM, using data of meter recharge information collected from Enugu Electricity Distribution Company (EEDC). …”
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    Article
  15. 1075

    Optimizing EV charging stations and power trading with deep learning and path optimization. by Qing Zhu

    Published 2025-01-01
    “…Path optimization, using the Dijkstra algorithm, minimized travel times for EV users by 11.4%. …”
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    Article
  16. 1076

    Enhancing Global Optimization through the Integration of Multiverse Optimizer with Opposition-Based Learning by Vu Hong Son Pham, Nghiep Trinh Nguyen Dang, Van Nam Nguyen

    Published 2024-01-01
    “…The effectiveness of iMVO is assessed through a series of tests involving both classical and IEEE CEC 2021 benchmark functions, demonstrating competitive performance against established algorithms. Moreover, the applicability of iMVO to real-world challenges is validated through its successful deployment in civil engineering tasks, particularly in optimizing truss designs and managing time-cost tradeoffs. …”
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    Article
  17. 1077

    An effective and efficient hierarchical -means clustering algorithm by Jianpeng Qi, Yanwei Yu, Lihong Wang, Jinglei Liu, Yingjie Wang

    Published 2017-08-01
    “…Second, we propose an “optimized update principle” that leverages moved points updating incrementally instead of recalculating mean and SSE of cluster in k -means iteration to minimize computation cost. …”
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    Article
  18. 1078

    Efficient hybrid heuristic adopted deep learning framework for diagnosing breast cancer using thermography images by Ahmad Y. A. Bani Ahmad, Jafar A. Alzubi, Manimaran Vasanthan, Suresh Babu Kondaveeti, J. Shreyas, Thella Preethi Priyanka

    Published 2025-04-01
    “…Then, the optimal binary thresholding is done to segment the preprocessed images, where optimized the thresholding value using developed Rock Hyraxes Dandelion Algorithm Optimization (RHDAO). …”
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    Article
  19. 1079

    RTRS algorithm in low-power Internet of things by Yuchen CHEN, Yuan CAO, Laipeng ZHANG, Lianghui DING, Feng YANG

    Published 2019-12-01
    “…Considering the feature of periodical uplink data transmission in IEEE 802.11ah low-power wide area network (LWPAN),a real-time RAW setting (RTRS) algorithm was proposed.Multiple node send data to an access point (AP),and the uplink channel resources were divided into Beacon periods in time.During a Beacon period,AP firstly predicted the next data uploading time and the total amount of devices that will upload data in the next Beacon period.The AP calculated the optimal RAW parameters for minimum energy cost and broadcasted the information to all node.Then all devices upload data according to the RAW scheduling.The simulation results show that the current network state can be predicted accurately according to the upload time of the terminal in the last period.According to the predicted state,raw configuration parameters can be dynamically adjusted and the energy efficiency can be significantly improved.…”
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    Article
  20. 1080

    RTRS algorithm in low-power Internet of things by Yuchen CHEN, Yuan CAO, Laipeng ZHANG, Lianghui DING, Feng YANG

    Published 2019-12-01
    “…Considering the feature of periodical uplink data transmission in IEEE 802.11ah low-power wide area network (LWPAN),a real-time RAW setting (RTRS) algorithm was proposed.Multiple node send data to an access point (AP),and the uplink channel resources were divided into Beacon periods in time.During a Beacon period,AP firstly predicted the next data uploading time and the total amount of devices that will upload data in the next Beacon period.The AP calculated the optimal RAW parameters for minimum energy cost and broadcasted the information to all node.Then all devices upload data according to the RAW scheduling.The simulation results show that the current network state can be predicted accurately according to the upload time of the terminal in the last period.According to the predicted state,raw configuration parameters can be dynamically adjusted and the energy efficiency can be significantly improved.…”
    Get full text
    Article