Multi-Objective Decision Support for Irrigation Systems Based on Skyline Query
Source abstract
Abstract
The steady increase in droughts worldwide has compelled many researchers to focus on water allocation. Multi-objective decision support for irrigation systems is a popular topic due to its relevance to the national economy and food supply. However, the majority of researchers have relied on conventional top-k designs for their decision support systems despite their limitations with regard to multi-objective systems. Thus, we propose applying a skyline query to the problem. As the input and output formats of skyline queries differ significantly from those of existing systems, we developed a new genetic algorithm and objective ranking. Qualitative and quantitative experiments using real-world data from Taiwan’s largest irrigated region demonstrate the effectiveness of the proposed approach.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Data Management and Algorithms · Data Mining Algorithms and Applications · Advanced Database Systems and Queries
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Industrial Engineering and Management, National Yunlin University of Science & Technology, Yunlin County 64002, Taiwan
Department of Computer Science and Engineering, National Chung Hsing University, Taichung City 402202, Taiwan
Automotive Research & Testing Center, Changhua County 50544, Taiwan
Funding
National Science and Technology Council
References (64)
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