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Статті в журналах з теми "Improved Intelligent Water Drop Algorithm"

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Wang, Tao, Jing Ni, and Yixuan Wang. "An Intelligent Water Drop Algorithm for Solving Multi-Objective Vehicle Routing Problems With Mixed Time Windows." International Journal of Strategic Decision Sciences 10, no. 1 (2019): 82–104. http://dx.doi.org/10.4018/ijsds.2019010106.

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This article proposes an Intelligent Water Drop Algorithm for solving Multi-Objective Vehicle Routing Problems by considering the constraints of vehicle volume, delivery mileage, and mixed time windows and minimizing the cost of distribution and the minimum number of vehicles. This article improves the basic Intelligent Water Drop Algorithm and show the improved intelligent water droplet genetic hybrid algorithm is an effective method for solving discrete problems. The authors present a practical example and show the applicability of the proposed algorithm. The authors compare the algorithms w
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Dr.K.Lenin. "REDUCTION OF ACTIVE POWER LOSS BY IMPROVED INTELLIGENT WATER DROP ALGORITHM." International Journal of Research - Granthaalayah 5, no. 11 (2017): 116–25. https://doi.org/10.5281/zenodo.1069332.

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In this paper, Improved Intelligent Water Drop (IIW) algorithm has been proposed to solve the optimal reactive power problem. In this work firefly and water drop algorithm has been combined to improve the exploration & exploitation. Fire fly algorithm imitates the firefly light flashing behaviour is an astonishing signal in the sky, usually found in tropical and temperate regions.  Water drop algorithm contains a few necessary elements of natural water drops and action and reaction that occur between river bed & the water drops that flow within.  Proposed Improved Intelligent
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Lenin, K. "REDUCTION OF ACTIVE POWER LOSS BY IMPROVED INTELLIGENT WATER DROP ALGORITHM." International Journal of Research -GRANTHAALAYAH 5, no. 11 (2017): 116–25. http://dx.doi.org/10.29121/granthaalayah.v5.i11.2017.2335.

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Анотація:
In this paper, Improved Intelligent Water Drop (IIW) algorithm has been proposed to solve the optimal reactive power problem. In this work firefly and water drop algorithm has been combined to improve the exploration & exploitation. Fire fly algorithm imitates the firefly light flashing behaviour is an astonishing signal in the sky, usually found in tropical and temperate regions. Water drop algorithm contains a few necessary elements of natural water drops and action and reaction that occur between river bed & the water drops that flow within. Proposed Improved Intelligent Water Drop
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Chen, Gang, Xiaoyuan Wu, Jinghua Li, and Hui Guo. "Green Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center Based on Improved Intelligent Water Drop Algorithms." Mathematical Problems in Engineering 2020 (January 9, 2020): 1–13. http://dx.doi.org/10.1155/2020/9839634.

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The timeliness of the steel distribution center process contributes to the smooth progress of ship construction. However, carbon emissions from vehicles in the distribution process are a major source of pollution. Reasonable vehicle routing and scheduling can effectively reduce the carbon emissions of vehicles and ensure the timeliness of distribution. To solve this problem, a green vehicle routing and scheduling problem model with soft time windows was proposed in this study. An intelligent water drop algorithm was designed and improved and then compared with the genetic algorithm and the tra
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Li, Jinghua, Hui Guo, Qinghua Zhou, and Boxin Yang. "Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode." Sustainability 11, no. 15 (2019): 4248. http://dx.doi.org/10.3390/su11154248.

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Анотація:
Timeliness of steel distribution centers can effectively ensure the smooth progress of ship construction, but the carbon emissions of vehicles in the distribution process are also a major source of pollution. Therefore, when considering the common cost of vehicle distribution, taking the carbon emissions of vehicles into account, this paper establishes a Mixed Integer Linear Programming (MILP) model called green vehicle routing and scheduling problem with simultaneous pickups and deliveries and time windows (GVRSP-SPDTW). An intelligent water drop algorithm is designed and improved, and compar
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Siddique, Nazmul, and Hojjat Adeli. "Water Drop Algorithms." International Journal on Artificial Intelligence Tools 23, no. 06 (2014): 1430002. http://dx.doi.org/10.1142/s0218213014300026.

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This article presents a review of a novel nature-inspired adaptive optimization algorithm known as Water Drop Algorithm (WDA) which imitates the dynamics of river systems and the behavior of water drops when they are moving in a river system such as the variation of velocity, the change of sediment/soil in the river bed, the change of direction of the flow, and so on. Recent improved, modified, and adaptive WDAs are examined in this paper. Various applications of WDA are described briefly including the vehicle routing problem, economic load dispatch problem, economic and emission dispatch prob
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Alhenawi, Esra’a, Hadeel Alazzam, Rizik Al-Sayyed, Orieb AbuAlghanam, and Omar Adwan. "Hybrid Feature Selection Method for Intrusion Detection Systems Based on an Improved Intelligent Water Drop Algorithm." Cybernetics and Information Technologies 22, no. 4 (2022): 73–90. http://dx.doi.org/10.2478/cait-2022-0040.

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Abstract A critical task and a competitive research area is to secure networks against attacks. One of the most popular security solutions is Intrusion Detection Systems (IDS). Machine learning has been recently used by researchers to develop high performance IDS. One of the main challenges in developing intelligent IDS is Feature Selection (FS). In this manuscript, a hybrid FS for the IDS network is proposed based on an ensemble filter, and an improved Intelligent Water Drop (IWD) wrapper. The Improved version from IWD algorithm uses local search algorithm as an extra operator to increase the
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Luangpaiboon, Pongchanun. "Optimisation of Manufacturing Process Models via Intelligent Water Drop Algorithm." Applied Mechanics and Materials 217-219 (November 2012): 1501–5. http://dx.doi.org/10.4028/www.scientific.net/amm.217-219.1501.

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In this paper, an intelligent water drop algorithm or IWD has been developed to optimise machining parameters in turning operation including a spring force model. Firstly, machining conditions are to minimise the production cost in conventional manufacturing processes. Several passes of rough machining are started on the turning operation with a final pass of a finishing. Various constraints are considered in each non-linear and non-convex model. The machining parameters in the turning consist of the depth of cut, cutting speed and feed. Finally, in a specialised manufacturing application on t
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Msallam, Mohammed M., and Mohammad Hamdan. "Improved intelligent water drops algorithm using adaptive schema." International Journal of Bio-Inspired Computation 3, no. 2 (2011): 103. http://dx.doi.org/10.1504/ijbic.2011.039909.

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Vaiyapuri, Thavavel, M. Sivakumar, Shridevi S, et al. "An intelligent water drop algorithm with deep learning driven vehicle detection and classification." AIMS Mathematics 9, no. 5 (2024): 11352–71. http://dx.doi.org/10.3934/math.2024557.

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<abstract> <p>Vehicle detection in Remote Sensing Images (RSI) is a specific application of object recognition like satellite or aerial imagery. This application is highly beneficial in different fields like defense, traffic monitoring, and urban planning. However, complex particulars about the vehicles and the surrounding background, delivered by the RSIs, need sophisticated investigation techniques depending on large data models. This is crucial though the amount of reliable and labelled training datasets is still a constraint. The challenges involved in vehicle detection from th
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Частини книг з теми "Improved Intelligent Water Drop Algorithm"

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Martinez, Diana, and Fevrier Valdez. "An Improved Intelligent Water Drop Algorithm to Solve Optimization Problems." In Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17747-2_19.

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Islam, Mohammad Raihanul, and M. Sohel Rahman. "An Improved Intelligent Water Drop Algorithm for a Real-Life Waste Collection Problem." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38715-9_56.

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Niu, S. H., S. K. Ong, and A. Y. C. Nee. "Improved Intelligent Water Drops Optimization Algorithm for Achieving Single and Multiple Objective Job Shop Scheduling Solutions." In Handbook of Manufacturing Engineering and Technology. Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-4670-4_25.

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Niu, S. H., S. K. Ong, and A. Y. C. Nee. "An Improved Intelligent Water Drops Optimization Algorithm for Achieving Single and Multiple Objective Job Shop Scheduling Solutions." In Handbook of Manufacturing Engineering and Technology. Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-4976-7_25-1.

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Dass, Anuli, Smriti Srivastava, and Monika Gupta. "Identification of Dynamic Systems Using Intelligent Water Drop Algorithm." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1822-1_34.

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Kumar, Manish, Srikant Jayaraman, Shikha Bhat, Shameek Ghosh, and V. K. Jayaraman. "Variable Selection and Fault Detection Using a Hybrid Intelligent Water Drop Algorithm." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1602-5_25.

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Liu, Huan, Lijing Tan, Luoxin Jin, and Ben Niu. "Improved Water Cycle Algorithm and K-Means Based Method for Data Clustering." In Intelligent Computing Methodologies. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60796-8_50.

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Sensarma, Debajit, and Koushik Majumder. "IWDRA: An Intelligent Water Drop Based QoS-Aware Routing Algorithm for MANETs." In Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2013. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02931-3_37.

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Petwal, Hemant, and Rinkle Rani. "An Improved Multi-objective Water Cycle Algorithm to Modify Inconsistent Matrix in Analytic Hierarchy Process." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4087-9_16.

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Crawford, Broderick, Ricardo Soto, Jorge Córdova, and Eduardo Olguín. "A Nature Inspired Intelligent Water Drop Algorithm and Its Application for Solving The Set Covering Problem." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33625-1_39.

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Тези доповідей конференцій з теми "Improved Intelligent Water Drop Algorithm"

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Xiong, Lei, XiangSheng Feng, LingLin Zhang, Quan Sun, and HuCheng Ren. "Semantic Segmentation Algorithm of Nighttime Road Surface Water Based on Improved Low-Light Image Enhancement." In 2024 5th International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI). IEEE, 2024. https://doi.org/10.1109/ichci63580.2024.10807993.

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Sun, Xixia, Su Pan, Chao Cai, Yanfang Chen, and Jie Chen. "Unmanned Aerial Vehicle Path Planning Based on Improved Intelligent Water Drop Algorithm." In 2018 Eighth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC). IEEE, 2018. http://dx.doi.org/10.1109/imccc.2018.00184.

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Wu, Jinchao, Yuncan Xue, and Enpeng Qiu. "Research on Unmanned Surface Vehicle Path Planning Based on Improved Intelligent Water Drops Algorithm." In EITCE 2020: 2020 4th International Conference on Electronic Information Technology and Computer Engineering. ACM, 2020. http://dx.doi.org/10.1145/3443467.3443827.

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Booyavi, Zahra, Ehsan Teymourian, G. M. Komaki, and S. Sheikh. "An improved optimization method based on the intelligent water drops algorithm for the vehicle routing problem." In 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS). IEEE, 2014. http://dx.doi.org/10.1109/cipls.2014.7007162.

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Faizah, N., C. Tan, A. S. Tan, et al. "Real-Time Edge Intelligence and Remotely Controlled Optimization of Intelligent Completion Injectivity." In GOTECH. SPE, 2024. http://dx.doi.org/10.2118/219272-ms.

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Abstract Intelligent completion injectivity refers to controlling and monitoring fluids injected into reservoirs to enhance oil and gas production at nearby producers. Traditional methods often lack the precision and adaptability required to optimize multi zonal injectivity effectively, particularly in the activation of flow control valves (FCV) to optimize production or injection. In conventional operations, these valves are activated manually on-site by a delayed chain of instruction decided on in town and communicated to an on-site technician. This must be done physically on unmanned platfo
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Crawford, Broderick, Ricardo Soto, Gino Astorga, and Eduardo Olguin. "Intelligent water drop algorithm (IWD)to solve software project scheduling problem." In 2016 11th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2016. http://dx.doi.org/10.1109/cisti.2016.7521467.

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Chengcheng, Dai. "Research on E-commerce Path Optimization Based on Intelligent Water Drop Algorithm." In ICIIP '22: 2022 7th International Conference on Intelligent Information Processing. ACM, 2022. http://dx.doi.org/10.1145/3570236.3570273.

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Rui, Ma, Du Jie, Gu Yunhua, and Yan Yunyang. "An Improved Drop-fall Algorithm Based on Background Analysis for Handwritten Digits Segmentation." In 2009 WRI Global Congress on Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/gcis.2009.60.

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Shi, Yifeng, Xiangsheng Feng, Yongjian Li, and Hao Li. "Pavement Area Water Detection Algorithm Based on Improved DEEPLABV3+." In CCRIS'22: 2022 3rd International Conference on Control, Robotics and Intelligent System. ACM, 2022. http://dx.doi.org/10.1145/3562007.3562025.

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Yang Jie, Yang Shenyuan, and Wei Na. "An improved Water Filling algorithm over time varying fading channel." In 2008 7th World Congress on Intelligent Control and Automation. IEEE, 2008. http://dx.doi.org/10.1109/wcica.2008.4594433.

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