کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
568329 1452269 2016 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
System learning approach to assess sustainability and forecast trends in regional dynamics: The San Luis Basin study, Colorado, U.S.A
ترجمه فارسی عنوان
رویکرد یادگیری سیستم برای ارزیابی پایداری و روند پیش بینی در پویایی منطقه ای: مطالعه حوضه سن لوئیس، کلرادو، U.S.A
کلمات کلیدی
شبکه های عصبی مصنوعی؛ اطلاعات فیشر؛ پیش بینی؛ سناریوی پایه؛ پایداری؛ سیستم منطقه ای
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزار
چکیده انگلیسی


• Novel methodology that combines principles of Artificial Neural Networks and Information Theory.
• A baseline scenario for the San Luis agricultural region was projected (1969–2025) with a sustainability constraint.
• Useful approach for sustainable management and decision making about consumption and production in complex human systems.

This paper presents a methodology that combines the power of an Artificial Neural Network and Information Theory to forecast variables describing the condition of a regional system. The novelty and strength of this approach is in the application of Fisher information, a key method in Information Theory, to preserve trends in the historical data and prevent over fitting projections. The methodology was applied to demographic, environmental, food and energy consumption, and agricultural production in the San Luis Basin regional system in Colorado, U.S.A. These variables are important for tracking conditions in human and natural systems. However, available data are often so far out of date that they limit the ability to manage these systems. Results indicate that the approaches developed provide viable tools for forecasting outcomes with the aim of assisting management toward sustainable trends. This methodology is also applicable for modeling different scenarios in other dynamic systems.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Environmental Modelling & Software - Volume 81, July 2016, Pages 1–11
نویسندگان
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