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Titlebook: Decision Support Systems for Weed Management; Guillermo R. Chantre,José L. González-Andújar Book 2020 Springer Nature Switzerland AG 2020

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發(fā)表于 2025-3-21 17:31:37 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Decision Support Systems for Weed Management
編輯Guillermo R. Chantre,José L. González-Andújar
視頻videohttp://file.papertrans.cn/265/264292/264292.mp4
概述Discusses mathematical modeling as an excellent framework for weed management.Addresses integrated weed management tactics from both operational and strategic time planning perspectives.Assesses the e
圖書封面Titlebook: Decision Support Systems for Weed Management;  Guillermo R. Chantre,José L. González-Andújar Book 2020 Springer Nature Switzerland AG 2020
描述Weed management Decision Support Systems (DSS) are increasingly important computer-based tools for modern agriculture. Nowadays, extensive agriculture has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to maximize economic profit by preserving and enhancing agricultural systems. Although previous contributions focusing on weed biology and weed management provide valuable insight on many aspects of weed species ecology and practical guides for weed control, no attempts have been made to highlight the forthcoming importance of DSS in weed management.?.This book is a first attempt to integrate `concepts and practice’ providing a novel guide to the state-of-art of DSS and the future prospects which hopefully would be of interest to higher-level students, academics and professionals in related areas..
出版日期Book 2020
關鍵詞pest control; weed management; mathematical agriculture models; decision systems in agricutlure; environ
版次1
doihttps://doi.org/10.1007/978-3-030-44402-0
isbn_softcover978-3-030-44404-4
isbn_ebook978-3-030-44402-0
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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Decision Making in Radiation Oncologyement (IWM) studies are nonlinear, mixed integer and large scale, they are quite difficult to optimize. In this chapter, some basic elements of optimization are reviewed, with special emphasis in practical issues (modelling, programming), which are less covered than theoretical topics in the open literature.
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Optimization in Decision Support Systemsement (IWM) studies are nonlinear, mixed integer and large scale, they are quite difficult to optimize. In this chapter, some basic elements of optimization are reviewed, with special emphasis in practical issues (modelling, programming), which are less covered than theoretical topics in the open literature.
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Book 2020 has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to
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DRASTIC and PIRI GIS-Based Indexes: Assessing the Vulnerability and Risk of Groundwater Pollutionvide complementary information. Incorporating them into a decision support system would help policy makers to identify areas most vulnerable to groundwater pollution and develop herbicide usage guidelines that protect groundwater resources.
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