Academic literature on the topic 'Artificial irrigation'
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Journal articles on the topic "Artificial irrigation"
Han, Liang, Shi Chang Fu, and Hui Hui Hong. "A Study on the Intelligent Bladder Irrigation Technology." Applied Mechanics and Materials 551 (May 2014): 638–41. http://dx.doi.org/10.4028/www.scientific.net/amm.551.638.
Full textWassermann, G., and A. Schmidt-Kloiber. "Ephemeroptera and Odonata of an artificial Danube backwater irrigation system." River Systems 10, no. 1-4 (September 18, 1996): 493–96. http://dx.doi.org/10.1127/lr/10/1996/493.
Full textSao, Davy, Hirotaka Saito, Tasuku Kato, and Jirka Šimůnek. "Numerical Analysis of Soil Water Dynamics during Spinach Cultivation in a Soil Column with an Artificial Capillary Barrier under Different Irrigation Managements." Water 13, no. 16 (August 9, 2021): 2176. http://dx.doi.org/10.3390/w13162176.
Full textVivan, Rodrigo Ricci, Jussaro Alves Duque, Murilo Priori Alcalde, Marcus Vinicius Reis Só, Clóvis Monteiro Bramante, and Marco Antonio Hungaro Duarte. "Evaluation of Different Passive Ultrasonic Irrigation Protocols on the Removal of Dentinal Debris from Artificial Grooves." Brazilian Dental Journal 27, no. 5 (October 2016): 568–72. http://dx.doi.org/10.1590/0103-6440201600725.
Full textLepp, Jonathan Van. "Evidence for Artificial Irrigation in Amratian Art." Journal of the American Research Center in Egypt 32 (1995): 197. http://dx.doi.org/10.2307/40000839.
Full textKobayashi, Noriyuki, Masanori Katayama, Toshiko Kakihara, Yoshitaka Yoshitake, and Masaya Ueki. "Water Purification in Irrigation Tanks by Enhancing Photosynthesis of Phytoplankton by Artificial Irradiation." Journal of Rainwater Catchment Systems 11, no. 1 (2005): 25–29. http://dx.doi.org/10.7132/jrcsa.kj00004364681.
Full textPerea, R. González, E. Camacho Poyato, P. Montesinos, and J. A. Rodríguez Díaz. "Irrigation Demand Forecasting Using Artificial Neuro-Genetic Networks." Water Resources Management 29, no. 15 (September 20, 2015): 5551–67. http://dx.doi.org/10.1007/s11269-015-1134-4.
Full textMattar, M. A., A. A. Alazba, and T. K. Zin El-Abedin. "Forecasting furrow irrigation infiltration using artificial neural networks." Agricultural Water Management 148 (January 2015): 63–71. http://dx.doi.org/10.1016/j.agwat.2014.09.015.
Full textKamyshova, Galina Nickolaevna. "Application of artificial neural networks for irrigation control." Agrarian Scientific Journal, no. 4 (April 22, 2021): 84–88. http://dx.doi.org/10.28983/asj.y2021i4pp84-88.
Full textZhao, Zhiqiang, Fuchu Dai, Hong Min, and Xinbin Tu. "Field infiltration of artificial irrigation into thick loess." Engineering Geology 294 (December 2021): 106388. http://dx.doi.org/10.1016/j.enggeo.2021.106388.
Full textDissertations / Theses on the topic "Artificial irrigation"
Chatdarong, Virat 1978. "Artificial recharge for conjunctive use in irrigation : the San Joaquin Valley, California." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/17512.
Full textIncludes bibliographical references (leaf 60).
One classical solution for dealing with surface water fluctuation is to construct a surface reservoir. However, because a surface reservoir requires too much land and has high negative impact on the environment, the use of a natural aquifer as a subsurface reservoir is proposed. In this solution, restoration of water to an aquifer requires an artificial recharge method. It is deduced that for irrigation purposes, a direct surface recharge is the most appropriate method to use because of its low cost of construction, operation and maintenance. To store water for agriculture, the capacity to recharge water within a limited time is the most important characteristic determining the feasibility of artificial recharge. Regarding a direct surface method, this capability is mainly governed by soil properties, depth to groundwater table, and spacing between two adjacent recharge areas. Under proper conditions, sufficient amounts of recharge water can store for agricultural purposes within a region. This study shows that total costs to construct, operate and maintain artificial recharge facilities are relatively low compared to the benefits that are expected from the recharge project. This implies th, - an artificial recharge scheme is a practical way to restore water to an aquifer, and use it in conjunction with surface water for irrigation.
by Virat Chatdarong.
M.Eng.
GonÃalves, Fabricio Mota. "Tools for analysis of self-management and water use of sustainability in irrigation perimeters." Universidade Federal do CearÃ, 2014. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=16108.
Full textThis work aims to characterize the current stage of Irrigated Perimeters Federal government with a view to self-management process and present alternative of allocating water distribution in secondary irrigation canals. The research was divided into two themes. The first addressed the development of a methodology for evaluating the performance of Irrigated Perimeters from the creation of a statistical model Multivariate discriminant and an Artificial Neural Network using the performance indicators of irrigated public areas of the National Department of Works Against Drought (Dnocs) and Development Company of the SÃo Francisco and ParnaÃba (Codevasf) as a way to evaluate the prospect of self-management of the same. The second dealt with the optimization of water use, a case study at the Experimental Farm Curu Valley, belonging to the Federal University of CearÃ, in the area adjacent to the irrigated Curu Pentecost were accomplished. Based on information provided by the National Department of Works Against Drought (Dnocs) and Development Company of the SÃo Francisco and ParnaÃba (Codevasf), the key performance indicators relating to Self-Management of Irrigated Perimeters were evaluated. The Multivariate and discriminant analysis (AMD) technique Artificial Neural Networks (ANN) were used to separate the standards relating to the performance of Irrigated Perimeters linear character or not. RNA yielded the automatic identification of the pattern that belongs to each perimeter over time. Based on the results obtained in the multivariate discriminant analysis, we observed the Generation Revenue per Hectare (HRM) as the most important indicator in discriminatory process between Irrigated Perimeters regarding self-management. The perimeters with the best performance in relation to self-management were: Nilo Coelho, CuraÃÃ I Pirapora and ManiÃoba. Regarding the operationalization of water use, we used a mathematical model of linear programming to determine the most rational way to release water for irrigated areas. The allocation defined by mathematical modeling proved adequate for the needs of established cultures, showing the most rational use of water.
Este trabalho tem como objetivo caracterizar o estÃgio atual dos PerÃmetros Irrigados PÃblicos Federais com vistas ao processo de autogestÃo e apresentar alternativa de alocar a distribuiÃÃo de Ãgua em canais secundÃrios de irrigaÃÃo. A pesquisa foi dividida em dois temas. O primeiro abordou o desenvolvimento de uma metodologia de avaliaÃÃo de desempenho de PerÃmetros Irrigados a partir da criaÃÃo de um modelo estatÃstico Discriminante Multivariado e de uma Rede Neural Artificial utilizando os indicadores de desempenho dos perÃmetros pÃblicos irrigados do Departamento Nacional de Obras Contra as Secas (Dnocs) e da Companhia de Desenvolvimento do Vale do SÃo Francisco e ParnaÃba (Codevasf), como forma de avaliar a perspectiva da autogestÃo dos mesmos. O segundo tratou da otimizaÃÃo do uso da Ãgua, tendo sido realizado um estudo de caso na Fazenda Experimental Vale do Curu, pertencente à Universidade Federal do CearÃ, em Ãrea contÃgua ao PerÃmetro Irrigado Curu Pentecoste. Com base nas informaÃÃes disponibilizadas pelo Departamento Nacional de Obras Contra as Secas (Dnocs) e a Companhia de Desenvolvimento do Vale do SÃo Francisco e ParnaÃba (Codevasf), foram avaliados os principais indicadores de desempenho relativos à AutogestÃo dos PerÃmetros Irrigados. A AnÃlise Multivariada Discriminante (AMD) e a tÃcnica de Redes Neurais Artificiais (RNA) foram utilizadas para separar os padrÃes referentes ao desempenho dos PerÃmetros Irrigados de carÃter linear ou nÃo. A RNA proporcionou a identificaÃÃo automÃtica do padrÃo a que pertence cada perÃmetro no decorrer do tempo. Com base nos resultados obtidos na AnÃlise Multivariada Discriminante, observou-se o indicador GeraÃÃo de Receita por Hectare (GRH) como mais importante no processo discriminatÃrio entre os PerÃmetros Irrigados quanto à AutogestÃo. Os PerÃmetros com os melhores desempenhos em relaÃÃo à AutogestÃo foram: Nilo Coelho, CuraÃà I, Pirapora e ManiÃoba. Com relaÃÃo à operacionalizaÃÃo do uso da Ãgua, utilizou-se um modelo matemÃtico de programaÃÃo linear para determinar a forma mais racional de liberar Ãgua para as Ãreas irrigadas. A alocaÃÃo definida pela modelagem matemÃtica mostrou-se adequada para as necessidades das culturas estabelecidas, mostrando a utilizaÃÃo mais racional da Ãgua.
Prisilla, L., P. Simon Vasantha Rooban, and L. Arockiam. "A Novel Method for Water irrigation System for paddy fields using ANN." IJCSN, 2012. http://hdl.handle.net/10150/219532.
Full textWater is an essential resource in the earth. It is also essential for irrigation, so irrigation technique is essential for agriculture. To irrigate large area of lands is a tedious process. In our country farmers are not following proper irrigation techniques. Currently, most of the irrigation scheduling systems and their corresponding automated tools are in fixed rate. Variable rate irrigation is very essential not only for the improvement of irrigation system but also to save water resource for future purpose. Most of the irrigation controllers are ON/OFF Model. These controllers cannot give optimal results for varying time delays and system parameters. Artificial Neural Network (ANN) based intelligent control system is used for effective irrigation scheduling in paddy fields. The input parameters like air, temperature, soil moisture, radiations and humidity are modeled. Using appropriate method, ecological conditions, Evapotranspiration, various growing stages of crops are considered and based on that the amount of water required for irrigation is estimated. Using this existing ANN based intelligent control system, the water saving procedure in paddy field can be achieved. This model will lead to avoid flood in paddy field during the rainy seasons and save that water for future purposes.
Neto, OdÃlio Coimbra da Rocha. "Rede Neural artificial aplicado ao manejo de irrigaÃÃo." Universidade Federal do CearÃ, 2012. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7930.
Full textA irrigaÃÃo à uma das prÃticas culturais que mais influencia o aumento da produÃÃo. No entanto, para o sucesso desta prÃtica necessita-se determinar o tempo certo da aplicaÃÃo de Ãgua para evitar desperdÃcios. Com isso, o emprego de sensores de umidade, como os sensores capacitivos, para nÃveis reais de umidade do solo aliados a redes neurais artificiais (RNAs) que calculam tempo de irrigaÃÃo, podem ser uma aquisiÃÃo promissora para a automaÃÃo de sistemas de irrigaÃÃo. Desta forma, objetivou-se com o presente trabalho desenvolver uma RNA que estime o tempo de irrigaÃÃo e comparando-o com o tempo estimado pelo mÃtodo do balanÃo volumÃtrico para a cultura da melancia. Foram utilizadas RNAs do tipo perceptron de mÃltiplas camadas. Para o treinamento foram usados dados de manejos em Ãrea do PERÃMETRO IRRIGADO BAIXO ACARAà no estado do Cearà onde a umidade do solo à determinada por sensores capacitivos desenvolvidos pela Universidade Federal do Cearà (UFC). Foram testadas redes para as fases da cultura. A primeira fase determinada entre 0 e 30 dias apÃs a semeadura (DAS) e a segunda fase sendo de 31 à 60 DAS. Foram testadas redes com 2 e 4 entradas; com 5, 10 e 20 neurÃnios na camada intermediÃria (NCI) e 1.000, 5.000 e 10.000 iteraÃÃes. ApÃs os treinamentos, as redes neurais artificiais foram testadas em campo para a sua validaÃÃo, comparando as suas respostas em relaÃÃo ao mÃtodo do balanÃo hÃdrico volumÃtrico (BHV) para a segunda fase da cultura. Avaliando as redes com 2 e 4 entradas, observou-se que as redes de 4 entradas obtiveram menor erro quadrÃtico mÃdio, convergindo mais rapidamente para valores prÃximos a zero, quando comparadas Ãs redes de 2 entradas. Quanto ao NCI, nÃo houve mudanÃas entre as redes, dispensando a necessidade de programar redes maiores que 5 NCI para essa aplicaÃÃo. Para o nÃmero de Ãpocas de treinamento, a que obteve o melhor ajuste aos valores foram as redes com 10.000 iteraÃÃes para a primeira fase da cultura e 5.000 iteraÃÃes para a segunda fase da cultura. Com a etapa de campo pode-se constatar que nÃo houve diferenÃa estatÃstica entre os dois manejos adotados. Assim, a rede neural artificial mostrou-se eficiente para o manejo da irrigaÃÃo, mesmo tendo no experimento valores inÃditos ao treinamento. Neste trabalho pode-se concluir que a RNA de melhores respostas para a primeira fase da cultura apresentou a MLP 4-5-1 com 10.000 Ãpocas de treinamento e taxa de aprendizagem de 0,9 e para a segunda fase, MLP 4-5-1, com 10.000 Ãpocas de treinamento e taxa de aprendizagem de 0,9. Conclui-se tambÃm, com a etapa de campo, que a rede foi bem sucedida em calcular o tempo de irrigaÃÃo.
Irrigation is an agricultural practice that leads to high crop production, however the success of this practice depends largely on correct computation of the timing of the application to avoid excessive or deficit application. Thus, the use of moisture sensors, such as capacitive sensors for determining soil moisture combined with artificial neural networks (ANNs) to calculate irrigation time can be a promising tool for automation of irrigation systems. The objective of this work was to develop an ANN that estimate the irrigation time and to contrast the results with the management based on a volume balance method on a watermelon field. Multilayer perceptron types of ANNs were tested. For ANNs training, data obtained in previous harvest were used. The watermelon field was located in Baixo Acaraà Irrigation District in Cearà State â Brazil, where soil moisture was determined using capacitive sensors developed at the Universidade Federal do Cearà (UFC). Networks were tested for two growing stages. The first stage spanning from 0 to the 30th day after seeding (DAS) and the second stage from the 31st to 60th DAS at harvesting. Networks were tested with 2 and 4 inputs, with 5, 10 and 20 neurons in the intermediate layer (NIL) and 1,000, 5,000 and 10,000 epochs. Upon training, the artificial neural networks were field-tested for validation by comparing their responses to the volumetric water balance method (VWBM) for the second stage an succeeding crop cycle. It was found that networks with four entries presented the largest mean square error, converging rapidly to values close to zero, compared the networks with two entries. For the NIL, it was not found significant difference in the mean square error between all 3 tested architectures, therefore it was not necessary to test networks larger than 5 NIL for this application. For the number of training epochs, the one with the best fit values were networks with 10,000 epochs for the first stage of the crop cycle, and 5,000 epochs for the second stage of the crop cycle. It was found no statistical difference in watermelon yield between the two irrigation timing strategies tested (ANN and VWBM). Therefore the artificial neural network was efficient in irrigation management in the field even though the network was presented to some values not occurring during the training process. Thus, one can conclude that the ANN for best performance was a 4-5-1 with learning rate 0.9, and 10000 and 5000 training epochs, respectively in the first and second crop stage. In addition, it was found that the network successfully scheduled the irrigation during the validation process.
Viksten, Jeff. "Effects on Groundwater Composition by the Koga Irrigation Scheme." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-293425.
Full textTillgång till rent dricksvatten är en av de viktigaste resurserna för samhället såväl som varje enskild människa. Utan tillgång till rent dricksvatten kan hälsa och livs-kvalitet komma att påverkas av vattenburna patogener.I torra länder som Etiopien med periodisk torka har man gjort insatser för att hushålla med vattnet utöver regnperioderna. Ett exempel på detta är Kogadammen i Merawi, där en fördämning har konstruerats för att förse ett område med konst-bevattning. Genom bevattning ett område ändrar man de hydrologiska förhållanden som råder vilket gör att grundvattnets sammansättning kan komma att ändras.Denna rapport syftar till att försöka samla in data som stödjer teorin att konst-bevattningen i området påverkar grundvattnets sammansättning. Prover av grund-vatten och ytvatten samlades och jämfördes för att se om några slutsatser kunde dras. Också allmänna dricksvatten parametrar ingick såsom förekomsten av bio-logiska patogener. Antalet prover som tagits är ensamt inte tillräckligt för att dra slutsatser, men när de kombineras med data från tidigare fältarbete i området och litteraturstudier stödjer de antagandet om att konstbevattningen i området påverkar grundvattensammansättningen.
Muhammad, Omid H. "Élaboration d’un biofilm polybactérien artificiel comme modèle pour la décontamination endodontique." Thesis, Nice, 2016. http://www.theses.fr/2016NICE4022/document.
Full textManagement of infection is the key to a successful root canal treatment and development of a study model of endodontic biofilm which resemble structurally to its wild type counterpart seems crucial before any clinical application of different protocols. However, the in vitro reproduction of the root canal biofilm which consists of about 500 different bacterial species is very difficult. In laboratory MICORALIS (EA 7354) we were interested in conception of an artificial polybacterial. The bibliographical research allowed to choose S. salivarius, E. faecalis, F. nucleatum and P. gingivalis which are representatives of different groups of root canal biofilm colonizers. Following a series of periodic Scanning Electron Microscopies of samples and furthermore by help of FISH-Confocal imaging of 16S rRNA, we could prove the presence of these bacteria inside the biofilm structure and illustrate their distribution over the root canal system. In addition, it was possible also to confirm the maturation time needed to obtain the biofilm model, which is resistant enough to be used in vitro for endodontic disinfection investigation. After being characterized, we treated the model biofilm with different endodontic decontamination protocols
Goldowitz, Joshua 1959. "The chloride to bromide ratio as an environmental groundwater tracer, with a field study at the Wellton-Mohawk Irrigation and Drainage District." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277079.
Full textRalston, S. "A study of the ecology of benthic algae using artificial substrates in an irrigation canal of the Breede River, Western Cape, South Africa." Thesis, University of Cape Town, 1996. http://hdl.handle.net/11427/25987.
Full textWeissenborn, Richard Carl 1952. "Apparent fate of recharged nonpurgeable chlorinated organics." Thesis, The University of Arizona, 1988. http://hdl.handle.net/10150/276786.
Full textHoedjes, Johannes Cornelis Bernardus. "Estimation de l'évapotranspiration sur des surfaces irriguées en zones semi-arides : combinaison modélisation, télédétection et scintillométrie." Toulouse 3, 2007. http://www.theses.fr/2007TOU30330.
Full textClimate change, as well as socio-economic development, is likely to put an even greater strain on the already streched water resources in the arid and semi-arid regions of the world in the coming decades. To face up to the increasing demand for agricultural production, in combination with decrease in water available for irrigation, farmers in these regions will have to adopt measures that enable them to increase productivity levels, whilst using less water. In this respect, an accurate knowledge of the actual evapotranspiration of irrigated areas is of paramount importance for a better irrigation management
Books on the topic "Artificial irrigation"
Huang Huai Hai Pingyuan di xia shui ren gong bu gei. Beijing: Shui li dian li chu ban she, 1990.
Find full textSusong, David D. Water budget and simulation of one-dimensional unsaturated flow for a flood- and a sprinkler-irrigated field near Milford, Utah. Salt Lake City, Utah: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.
Find full textSusong, David D. Water budget and simulation of one-dimensional unsaturated flow for a flood- and a sprinkler-irrigated field near Milford, Utah. Salt Lake City, Utah: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.
Find full textSusong, David D. Water budget and simulation of one-dimensional unsaturated flow for a flood- and a sprinkler-irrigated field near Milford, Utah. Salt Lake City, Utah: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.
Find full textNew Mexico Water Resources Research Institute. Symposium. Water and science: Proceedings of the New Mexico Water Resources Research Institute Symposium : Macey Center, New Mexico Institute of Mining and Technology, Socorro, New Mexico, February 15, 1985. Edited by Harris Linda G. Las Cruces, N.M. (Box 3167, Las Cruces 88003): New Mexico Water Resources Research Institute, New Mexico State University, 1985.
Find full textHuang Huai Hai ping yuan di xia shui ren gong bu gei. Xin hua shu dian jing shou, 1990.
Find full textSeely, Harold E. Impact of artificial flooding on farm profits and streamflow in Echo Meadows, Oregon. 1997.
Find full textPost, Buckley, Schuh & Jernigan. and St. Johns River Water Management District (Fla.), eds. Water supply needs and sources assessment: Alternative water supply strategies investigation, assessment of the cost of supplying reclaimed water to areas of high agricultural withdrawals. Palatka, Fla: St. Johns River Water Management District, 1998.
Find full textSteenvoorden, J. H. A. M. and Endreny Theodore A. 1968-, eds. Wastewater re-use and groundwater quality. Wallingford, Oxfordshire, UK: International Association of Hydrological Sciences, 2004.
Find full textLyon, John G., Hugh Turral, Prasad Thenkabail, and Chandrashekhar Biradar. Remote Sensing of Global Croplands for Food Security. Taylor & Francis Group, 2009.
Find full textBook chapters on the topic "Artificial irrigation"
Laabidi, K., M. Khayyat, and T. Almohamadi. "Smart grid irrigation." In Innovative and Intelligent Technology-Based Services for Smart Environments – Smart Sensing and Artificial Intelligence, 217–22. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003181545-31.
Full textHashemi, Hossein, Sayyed Ahang Kowsar, Ronny Berndtsson, Xinping Wang, and Hiroshi Yasuda. "Using Floodwater for Artificial Recharge and Spate Irrigation." In Sustainable Water Resources Management, 697–736. Reston, VA: American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784414767.ch25.
Full textLi, Jianwen, Xihuan Sun, Juanjuan Ma, Xianghong Guo, and Jingling Li. "Intelligence Optimization in Parameter Identification of the Border Irrigation Model." In Artificial Intelligence and Computational Intelligence, 11–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23887-1_2.
Full textLi, Jingling, Xihuan Sun, Juanjuan Ma, Jie Cui, Qiuli Liu, and Xing Shen. "Modeling of Water Dynamics on Soil in Water Storage Pit Irrigation." In Artificial Intelligence and Computational Intelligence, 51–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23881-9_7.
Full textTan, Xiaoying, Gerd Reis, and Didier Stricker. "Convolutional Recurrent Neural Network for Bubble Detection in a Portable Continuous Bladder Irrigation Monitor." In Artificial Intelligence in Medicine, 57–66. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21642-9_9.
Full textVarshney, Kratika, Sweta Tripathi, and Vaibhav Purwar. "Expert System on Smart Irrigation Using Internet of Things." In Proceedings of International Conference on Communication and Artificial Intelligence, 181–88. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6546-9_19.
Full textBentabet, Dougani. "Cloud-IoT Platform for Smart Irrigation Solution Based on NodeMCU." In Artificial Intelligence and Renewables Towards an Energy Transition, 689–96. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63846-7_65.
Full textIslam, Sirajul, and Bipul Talukdar. "Application of Artificial Immune System in Optimal Design of Irrigation Canal." In Nature-Inspired Methods for Metaheuristics Optimization, 169–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-26458-1_10.
Full textMostefaoui, Zineb, and Sofiane Amara. "Optimization of Irrigation with Photovoltaic System in the Agricultural Farms - Greenhouse: Case Study in Sahara (Adrar)." In Artificial Intelligence in Renewable Energetic Systems, 401–8. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73192-6_42.
Full textKlyushin, Dmitriy, and Andrii Tymoshenko. "Optimization of Drip Irrigation Systems Using Artificial Intelligence Methods for Sustainable Agriculture and Environment." In Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications, 3–17. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51920-9_1.
Full textConference papers on the topic "Artificial irrigation"
Mpallas, L., C. Tzimopoulos, and C. Evangelidis. "Rainfall data calculation using Artificial Neural Networks and adaptive neuro-fuzzy inference systems." In SUSTAINABLE IRRIGATION 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/si100121.
Full textSahany, Siddharth, Biswaranjan Swain, Jayshree Halder, Praveen Priyaranjan Nayak, and Satyanarayan Bhuyan. "Artificial Intelligence based Bot Assisted Irrigation System." In 2021 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology(ODICON). IEEE, 2021. http://dx.doi.org/10.1109/odicon50556.2021.9428975.
Full textAggarwal, Sachin, and Anil Kumar. "A Smart Irrigation System to Automate Irrigation Process Using IOT and Artificial Neural Network." In 2019 2nd International Conference on Signal Processing and Communication (ICSPC). IEEE, 2019. http://dx.doi.org/10.1109/icspc46172.2019.8976631.
Full textHeendeniya, H. K. C. B., R. M. M. Ruwanthika, and A. G. Buddhika P. Jayasekara. "Potential for improving green roof performance through artificial irrigation." In 2016 Moratuwa Engineering Research Conference (MERCon). IEEE, 2016. http://dx.doi.org/10.1109/mercon.2016.7480130.
Full textAngelin Blessy, J., and Anveesh kumar. "Smart Irrigation System Techniques using Artificial Intelligence and IoT." In 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV). IEEE, 2021. http://dx.doi.org/10.1109/icicv50876.2021.9388444.
Full textYu, Chuang, Yi Wu, and Yang Yu. "Intelligent Irrigation System Based on Fuzzy Control." In 2010 International Conference on Artificial Intelligence and Computational Intelligence (AICI). IEEE, 2010. http://dx.doi.org/10.1109/aici.2010.347.
Full textJan Franklin Adamowski, Hiu Fung Chan, and Inmaculada Pulido-Calvo. "Irrigation Water Demand Forecasting Using Wavelet Transforms and Artificial Intelligence." In 2011 Louisville, Kentucky, August 7 - August 10, 2011. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2011. http://dx.doi.org/10.13031/2013.38174.
Full textVijay, Anil Kumar Saini, Susmita Banerjee, and Himanshu Nigam. "An IoT Instrumented Smart Agricultural Monitoring and Irrigation System." In 2020 International Conference on Artificial Intelligence and Signal Processing (AISP). IEEE, 2020. http://dx.doi.org/10.1109/aisp48273.2020.9073605.
Full textKawai, Takaaki, and Hiroshi Mineno. "Evaluation environment using edge computing for artificial intelligence-based irrigation system." In 2020 16th International Conference on Mobility, Sensing and Networking (MSN). IEEE, 2020. http://dx.doi.org/10.1109/msn50589.2020.00046.
Full textPlotog, Ioan, Gaudentiu Varzaru, Bogdan Mihailescu, Beatrice Iacomi, Roxana Madjar, Cristian Iacomi, Viorel Popescu, and Catalin Sfetcu. "Small farm complex irrigation controller based on wireless communication." In 2015 7th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). IEEE, 2015. http://dx.doi.org/10.1109/ecai.2015.7301142.
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