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Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence
Field Canals Improvement Projects is an important sustainable project to save fresh water in our world. Machine learning and artificial intelligence (AI) needs sufficient dataset size to model and predict the cost and duration of Field Canals Improvement Projects. Therefore, this data paper presents...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Elsevier
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256293/ https://www.ncbi.nlm.nih.gov/pubmed/32490068 http://dx.doi.org/10.1016/j.dib.2020.105688 |
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author | Elmousalami, Haytham H. |
author_facet | Elmousalami, Haytham H. |
author_sort | Elmousalami, Haytham H. |
collection | PubMed |
description | Field Canals Improvement Projects is an important sustainable project to save fresh water in our world. Machine learning and artificial intelligence (AI) needs sufficient dataset size to model and predict the cost and duration of Field Canals Improvement Projects. Therefore, this data paper presents dataset includes the key parameters of such project to be used for analyzing and modelling project cost and duration. The data were acquired based on questionnaire survey and collecting historical cases of Field Canals Improvement Projects. The data consists of the following features: area served, total length of PVC pipe line, number of irrigation values, construction year, geographical zone, cost of FCIP, and duration of FCIP construction. The data can be applied to compare and evaluate the performance of machine learning algorithms for predicting cost and duration. |
format | Online Article Text |
id | pubmed-7256293 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-72562932020-06-01 Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence Elmousalami, Haytham H. Data Brief Business, Management and Accounting Field Canals Improvement Projects is an important sustainable project to save fresh water in our world. Machine learning and artificial intelligence (AI) needs sufficient dataset size to model and predict the cost and duration of Field Canals Improvement Projects. Therefore, this data paper presents dataset includes the key parameters of such project to be used for analyzing and modelling project cost and duration. The data were acquired based on questionnaire survey and collecting historical cases of Field Canals Improvement Projects. The data consists of the following features: area served, total length of PVC pipe line, number of irrigation values, construction year, geographical zone, cost of FCIP, and duration of FCIP construction. The data can be applied to compare and evaluate the performance of machine learning algorithms for predicting cost and duration. Elsevier 2020-05-19 /pmc/articles/PMC7256293/ /pubmed/32490068 http://dx.doi.org/10.1016/j.dib.2020.105688 Text en © 2020 The Author http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Business, Management and Accounting Elmousalami, Haytham H. Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence |
title | Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence |
title_full | Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence |
title_fullStr | Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence |
title_full_unstemmed | Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence |
title_short | Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence |
title_sort | data on field canals improvement projects for cost prediction using artificial intelligence |
topic | Business, Management and Accounting |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256293/ https://www.ncbi.nlm.nih.gov/pubmed/32490068 http://dx.doi.org/10.1016/j.dib.2020.105688 |
work_keys_str_mv | AT elmousalamihaythamh dataonfieldcanalsimprovementprojectsforcostpredictionusingartificialintelligence |