Academic literature on the topic 'Intelligent Water Drop Algorithm'

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Journal articles on the topic "Intelligent Water Drop Algorithm"

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AlDeeb, Bashar Abedal Mohdi, Norita Md Norwawi, and Mohammed A. Al-Betar. "A Survey on Intelligent Water Drop Algorithm." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 13, no. 10 (2014): 5075–84. http://dx.doi.org/10.24297/ijct.v13i10.2329.

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In the optimization areas, there are different algorithms that have been applied such as swarm intelligence algorithms. The researchers have found different algorithms by simulating the behaviors of various swarms of insects and animals such as fishes, bees, and ants. The intelligent water drops algorithm is one of the recently developed algorithms in the swarm intelligence field; this algorithm mimicked the dynamic of river systems. The natural water drops used to develop Intelligent Water Drop (IWD) algorithm. Therefore, the mechanisms that happen in rivers have inspired the researchers mainly to create new algorithms. IWD is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to a better drops (or solutions). This paper presents recent developments of the IWD algorithms in terms of theory and application. This paper concludes many of research directions that are necessary for the future of IWD 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 with the basic algorithm and show the improved intelligent droplet genetic hybrid algorithm has higher computing efficiency and continuous optimization capability.
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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 Water Drop (IIW) algorithm has been tested in Standard IEEE 57,118 bus systems & real power loss has been comparatively reduced with voltage profiles are within the limits.
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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 traditional intelligent water drop algorithm. The applicability of the improved intelligent water drop algorithm was demonstrated. Finally, this algorithm was applied to a specific example to demonstrate that the improved intelligent water drop algorithm effectively reduced the cost of such green vehicle problems, thus reducing the carbon emissions of vehicles during the distribution process and achieving reductions in environmental pollution. Ultimately, this algorithm facilitates the achievement of green shipbuilding.
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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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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 (IIW) algorithm has been tested in Standard IEEE 57,118 bus systems & real power loss has been comparatively reduced with voltage profiles are within the limits.
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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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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 compared with the genetic algorithm and traditional intelligent water drop algorithm. The applicability of the improved intelligent water drop algorithm is proven. Finally, it is applied to a specific example to prove that the improved intelligent water drop algorithm can effectively reduce the cost of such problems, thereby reducing the carbon emissions of vehicles in the distribution process, achieving the goals of reducing environmental pollution and green shipbuilding.
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Abdous, Majid, and Touraj Banirostam. "Cloud Computing Intelligent Management by Metaheuristic Algorithm of Intelligent Water Drop." IJARCCE 5, no. 3 (2016): 1–6. http://dx.doi.org/10.17148/ijarcce.2016.5301.

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Shah‐Hosseini, Hamed. "Intelligent water drops algorithm." International Journal of Intelligent Computing and Cybernetics 1, no. 2 (2008): 193–212. http://dx.doi.org/10.1108/17563780810874717.

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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 problem, optimal data aggregation tree in wireless networks, reactive power dispatch problem service selection, and reservoir operation.
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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 the spring force problem, an achievement of a specific goal may be the primary objective subject to some process parameter ranges. The computational results clearly showed that the proposed sequential procedures of the IWD have considerably improved the objective functions.
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Dissertations / Theses on the topic "Intelligent Water Drop Algorithm"

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Lundholm, Jesper, and Johan Ledéus. "A comparison of Intelligent Water Drops and Genetic Algorithm for maze solving." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229737.

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Evolutionary and swarm based algorithms are subsets of bio-inspired algorithms where    Genetic Algorithm (GA) belongs to the former and Intelligent Water Drops (IWD) to the latter.      In this report we investigate their ability to solve mazes with different complexity.    As performance measures we compare solution quality and success rates.    We find that IWD outperforms GA on mazes of low complexity but results deteriorate quickly as maze complexity increases. GA produces more stable results, better solution quality and a higher success rate for high complexity mazes. Some potential improvements inspired by other works are discussed. We conclude that examining different improvements through stronger subordinate problem-specific heuristics is of interest.<br>Inom de bio-inspirerade algoritmerna finns bland annat evolutionära och svärmbaserade algoritmer. Genetisk Algoritm (GA) tillhör den förra och Intelligenta Vattendroppar (IWD) den senare. I denna rapport undersöker vi dessa två algoritmers förmåga att lösa labyrinter av olika komplexitet. För att mäta prestandan jämförs lösningskvaliteten samt andelen lösningar där destinationen nås. Vi finner att     IWD utpresterar GA för labyrinter av låg komplexitet men resultaten försämras snabbt när komplexitetgraden stiger. För labyrinter av högre komplexitet producerar GA stabilare resultat med bättre lösningskvalitet och högre andel acceptabla lösningar. Några möjliga förbättringsåtgärder som inspirerats av andras rapporter diskuteras. Sammanfattningsvis fastslår vi att vidare undersökning av olika förbättringar genom starkare underordnade problemspecifika heuristiker är intressant.
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Vaddhireddy, Jyothirmye. "A Novel Swarm Intelligence based IWD Algorithm for Routing in MANETs." University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1321589580.

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Costa, BÃrbara Cristina Alves da. "Load measurement error influence on friction factor calibration of pipe water distribution networks through do reverse transient method and genetic algorithm." Universidade Federal do CearÃ, 2014. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=13621.

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O estudo de redes hidrÃulicas para fins de operaÃÃo ou anÃlise de viabilidade para ampliaÃÃo ou recuperaÃÃo das mesmas à iniciado pela calibraÃÃo, neste contexto, entendida como identificaÃÃo de parÃmetros tais como: fator de atrito, rugosidade e diÃmetro. O MÃtodo Transiente Inverso em conjunto com Algoritmo genÃtico se mostra eficiente nessa tarefa. O referido mÃtodo emprega o MÃtodo das CaracterÃsticas na soluÃÃo das equaÃÃes de movimento para escoamento transiente em tubos de redes e a otimizaÃÃo das soluÃÃes à baseada na Teoria Evolutiva e avaliada por uma funÃÃo objetivo, que neste estudo à o somatÃrio do mÃdulo da diferenÃa entre as cargas medidas e calculadas pelo modelo para cada conjunto de soluÃÃes. Considerando que o objetivo do desenvolvimento de modelos matemÃticos para a calibraÃÃo de redes hipotÃticas à a utilizaÃÃo dos mesmos em redes reais, e que nessas, a coleta de dados de carga està sujeita a erros de mediÃÃo, seja devido a defeitos nos equipamentos seja por condiÃÃes ambiente desfavorÃveis ou outros efeitos aleatÃrios e tendo em vista a relevÃncia dos fatores de atrito nas tubulaÃÃes, pela sua relaÃÃo com perdas de carga que devem ser controladas para um Ãtimo funcionamento de redes, garantindo um abastecimento contÃnuo em quantidade e condiÃÃes de funcionamento adequados, este trabalho propÃe-se a verificar a interferÃncia da presenÃa de erros de mediÃÃo de carga transiente na identificaÃÃo dos fatores de atrito em duas redes hidrÃulicas hipotÃticas. As mesmas sÃo de portes diferentes com relaÃÃo ao nÃmero de anÃis, nÃs e tubos. Ambas sÃo alimentadas por um reservatÃrio cada. As condiÃÃes transientes sÃo atribuÃdas a uma manobra de vÃlvula instalada em um dos nÃs de cada rede. A coleta de dados de carga à restrita a 20% dos nÃs de cada rede, sendo que um deles à o nà onde se encontra a vÃlvula. O tempo de observaÃÃo do transiente hidrÃulico à restrito ao tempo da manobra de vÃlvula, 20s, e ocorre em intervalos de 0,1s, resultando em 200 registros de carga. A condiÃÃo permanente das redes à inicialmente desconhecida o conhecimento acerca da mesma à restrito a carga nos reservatÃrios e demandas nos nÃs, bem como diÃmetros dos tubos, os fatores de atrito sÃo inicialmente estipulados. A determinaÃÃo das condiÃÃes permanente e transiente bem como a identificaÃÃo dos fatores de atrito à realizada com a utilizaÃÃo de um modelo hidrÃulico e geram cargas transientes que sÃo consideradas convencionalmente verdadeiras, essas entÃo recebem incrementos de diversos erros sistemÃticos e aleatÃrios, que geram novas cargas e essas sÃo consideradas coletadas com erros de mediÃÃo. A partir dessas novas cargas sÃo realizadas identificaÃÃes de fatores de atrito, os quais sÃo comparados com os que foram obtidos considerando um caso ideal de cargas sem erros de mediÃÃo. A referida comparaÃÃo à realizada atravÃs do Erro MÃdio Relativo e da FunÃÃo Objetivo Ãtima. Os resultados encontrados demonstram que os erros de mediÃÃo interferem na identificaÃÃo dos fatores de atrito apesar de nÃo ser possÃvel delinear uma relaÃÃo entre os mesmos.<br>The study of hydraulic networks for operation purposes or viability analysis for extension or renovation of the same is started the calibration in this context understood as identification parameters, such as friction coefficient, surface roughness and diameter. The Transient Inverse Method in conjunction with genetic algorithm is efficient in this task shows. This method employs the method of characteristics in the solution of the equations of motion for transient flow in networks of pipes and the optimization of solutions is based on Evolutionary Theory and evaluated by an objective function, which in this study is the sum of the difference between the module loads measured and calculated by the model for each set of solutions. Whereas the objective of the development of mathematical models for calibration hypothetical networks is their use in real networks, and that these, the collection of payload data is subject to measurement errors, is due to defects in the equipment or by conditions unfavorable environment or other random effects and taking into account the relevance of friction factors in pipelines, by their relationship to head losses that must be controlled to a great operation of networks, ensuring a continuous supply in quantity and appropriate operating conditions, this work is proposed to verify the influence of the presence of transient load measurement errors in the identification of friction factors in two hypothetical hydraulic networks. They are of different sizes with the number of rings, knots and tubes. Both are each fed by a reservoir. The transient conditions are assigned to a valve maneuver installed in one of the nodes of each network. The load data collection is restricted to 20% of the nodes in each network, one of which is the node where the valve is located. The hydraulic transient observation time is restricted to the valve maneuver time, 20s, and occurs at intervals of 0.1s, resulting in 200 charge records. The permanent condition of networks is initially unknown knowledge about the same is restricted to load in the reservoirs and demands on us as well as pipe diameter, the friction factors are initially stipulated. The determination of the permanent and transient conditions and the identification of the friction factors is performed using a hydraulic model and generate transient loads which are conventionally considered true, then these various steps of receiving systematic and random errors, which generate new burdens and these are considered collected with measurement errors. From these new loads are carried IDs friction factors, which are compared with those obtained considering an ideal case with no measurement errors loads. This comparison is performed using the mean relative error and function great goal. The results show that measurement errors in the identification of interfering friction factors although not possible to draw a relationship between them.
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Peltonen, Joanna. "Development of effective algorithm for coupled thermal-hydraulics : neutron-kinetics analysis of reactivity transient." Licentiate thesis, Stockholm : Skolan för teknikvetenskap, Kungliga Tekniska högskolan, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-11033.

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Book chapters on the topic "Intelligent Water Drop Algorithm"

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Xing, Bo, and Wen-Jing Gao. "Intelligent Water Drops Algorithm." In Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03404-1_23.

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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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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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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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Y., Harish, Venkateshwarlu B., Chakravarthi Jada, Kranthi Kumar R., and Irfan Feroz G. "Intelligent Water Drops Algorithm for Multimodal Spaces." In Swarm, Evolutionary, and Memetic Computing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20294-5_2.

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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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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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Alijla, Basem O., Lim Chee Peng, Ahamad Tajudin Khader, and Mohammed Azmi Al-Betar. "Intelligent Water Drops Algorithm for Rough Set Feature Selection." In Intelligent Information and Database Systems. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36543-0_37.

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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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Aldeeb, Bashar A., Norita Md Norwawi, Mohammed A. Al-Betar, and Mohd Zalisham Bin Jali. "Solving University Examination Timetabling Problem Using Intelligent Water Drops Algorithm." In Swarm, Evolutionary, and Memetic Computing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20294-5_17.

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Conference papers on the topic "Intelligent Water Drop Algorithm"

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Thalji, Nisrean Jaber. "Exploring the Efficacy of Intelligent Water Drops Algorithm for Solving Nondeterministic Polynomial Problems." In 2024 7th International Conference on Internet Applications, Protocols, and Services (NETAPPS). IEEE, 2024. https://doi.org/10.1109/netapps63333.2024.10823522.

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Domnori, Elton, Donald Elmazi, and Gledi Tace. "Enhancing Water Resource Management through IoT-Enabled Smart Water Monitoring Systems: A Multi-Agent Algorithm Approach." In 2024 International Conference on INnovations in Intelligent SysTems and Applications (INISTA). IEEE, 2024. http://dx.doi.org/10.1109/inista62901.2024.10683848.

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Huang, Jinfei, Wenbin Chen, Hao Guo, et al. "Research on the structure of intelligent toilet water efficiency testing machine." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3040318.

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Huang, Jinfei, Wenbin Chen, Hao Guo, Huachao Lv, qiqi zhang, and Jian Zhou. "Application research of water efficiency test equipment for toilet flushing valve." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3040310.

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Gao, Ze, Baoxian Wang, Nana He, and Wei Zheng. "A disease detection method for tunnel water leakage based on Bayesian reasoning." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3039733.

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Feng, Nianshun, Jiaoyang Pu, Qinying Li, Xuejie Hu, Peiyu Liang, and Yue Tian. "Design of fast Fourier transform-digital beamforming-based algorithm on water level measurement." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3039391.

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Sofwan, Aghus, Damar Amarsa Ajiputra, M. Arfan, and Imam Santoso. "Design of Classification of Shrimp Pond Water Quality Based on Random Forest Algorithm." In 2024 International Seminar on Intelligent Technology and Its Applications (ISITIA). IEEE, 2024. http://dx.doi.org/10.1109/isitia63062.2024.10667998.

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Zheng, Zesen. "Water Flow Anomaly Data Detection Model Based on Hierarchical Clustering and DBSACAN Algorithm." In 2024 International Conference on Intelligent Computing and Data Analytics (ICDA). IEEE, 2024. https://doi.org/10.1109/icda64850.2024.00019.

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Huang, Zhijia, Kefan Cai, and Jinzi Li. "Research on Intelligent Water Management Detection Based on the K-means Clustering Algorithm." In 2025 International Conference on Electrical Drives, Power Electronics & Engineering (EDPEE). IEEE, 2025. https://doi.org/10.1109/edpee65754.2025.00024.

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Sun, Junqing, Hao Wang, and Hongbo Shang. "Intelligent identification method of coal seam roof water source based on random forest algorithm." In International Conference on Mechatronics and Intelligent Control (ICMIC 2024), edited by Kun Zhang and Pascal Lorenz. SPIE, 2025. https://doi.org/10.1117/12.3045147.

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