A practical surface irrigation design based on fuzzy logic and meta-heuristic algorithms

Pazouki, Ehsan

doi:10.1016/j.agwat.2021.107069

Cited by 11 publications

(6 citation statements)

References 32 publications

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“…Artificial neural networks and fuzzy logic on the other hand are systems that can be continuously trained in making prediction models for sustainable agriculture [ 21 ]. A recent 2021 stimulation study by Pazouki, devised a system for surface irrigation using fuzzy expert systems and meta-heuristic optimization algorithms which enhanced the regular system and improved its practicality, performance and reduced the requirement for manual labour [ 61 ]. Hence proving the wide application of the system in irrigation and water management for sustainable agriculture.…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

2022

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There is a dearth of literature that provides a bibliometric analysis concerning the role of Artificial Intelligence (AI) in sustainable agriculture therefore this study attempts to fill this research gap and provides evidence from the studies conducted between 2000–2021 in this field of research. The study is a systematic bibliographic analysis of the 465 previous articles and reviews done between 2000–2021 in relation to the utilization of AI in sustainable methods of agriculture. The results of the study have been visualized and presented using the VOSviewer and Biblioshiny visualizer software. The results obtained post analysis indicate that, the amount of academic works published in the field of AI’s role in enabling sustainable agriculture increased significantly from 2018. Therefore, there is conclusive evidence that the growth trajectory shows a significant climb upwards. Geographically analysed, the country collaboration network highlights that most number of studies in the realm of this study originate from China, USA, India, Iran, France. The co-author network analysis results represent that there are multi-disciplinary collaborations and interactions between prominent authors from United States of America, China, United Kingdom and Germany. The final framework provided from this bibliometric study will help future researchers identify the key areas of interest in research of AI and sustainable agriculture and narrow down on the countries where prominent academic work is published to explore co-authorship opportunities.

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Section: Discussionmentioning

confidence: 99%

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

2022

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“…Overall, research on fish quality using fuzzy methods is one way to evaluate fish quality more accurately (Dowlati et al, 2012). This method can be used by the fishing and fish processing industry to determine the quality of the products produced and make the right decisions (Pazouki, 2021;Wiratama et al, 2022). However, further research is still needed to evaluate the effectiveness of fuzzy methods in measuring the overall quality of fish.…”

Section: Literature Reviewmentioning

confidence: 99%

Determining Tilapia Quality Using the Fuzzy Logic

Slamet

Hindarto

Sumarno

2023

CNAHPC

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Fish are living things with the highest trophic level in a body of water. Fish are living creatures that live in aquatic environments in fresh, brackish and marine waters. Tilapia is one of the leading commodities of aquaculture and is a widely used freshwater fish, and its production is quite high. Fuzzy logic is a logic that deals with the concept of partial truth, where classical logic states that everything can be expressed in binary terms (0 or 1). Various theories in the development of fuzzy logic show that fuzzy logic can be used to model various systems. A very adaptable and data-tolerant approach is mamdani fuzzy. Therefore, in this research, a mamdani fuzzy model will be developed to evaluate the quality of tilapia. This research uses fuzzy logic to evaluate the quality of tilapia based on its texture, taste, and size. In this study, researchers modeled 4 fuzzy variables, with 3 inputs (texture, taste, and size), 1 output (price), and a total of 4 fuzzy variables. The MIN IMPLICATION function was used in the inference procedure in the fuzzy operator application. Next, the MAX approach is used in the compilation of all fuzzy outputs. Then comes the affirmation, also known as defuzzification which is done using the Centroid method. The results show with 10 trial data it is seen that the higher the input value of size, the higher the output value of price.

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“…However, irrigation projects are usually designed and managed for specific irrigation methods, and changing from gravity to pressurized irrigation systems can be unsuccessful and costly. Therefore, one alternative is improving the method of design in agriculture using new technologies (Araújo et al, 2019;Pazouki, 2021). Ayers & Westcot (1994), in the Morada Nova Irrigation Project (MNIP), with the sites indicated by circles, and the Kriging interpolation in the background Given the above, as groundwater exploitation in the MNIP is the only water resource currently available for the maintenance of agricultural activities, which have significant importance in the economic development of the region, it is urgent to adopt practices of soil management and water monitoring, qualitatively and quantitatively, that enable the continuity of production activities and protect the environment.…”

Section: Groundwater Quality For Irrigation Purposesmentioning

confidence: 99%

Groundwater resources for agricultural purposes in the Brazilian semi-arid region

Nunes

Costa

Cavalcante

et al. 2022

Rev. bras. eng. agríc. ambient.

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Exploitation of groundwater resources with no proper characterization of water reserves jeopardizes the quantity and quality of water available in the future. A major challenge is finding appropriate methods or coefficients to evaluate the carrying capacity of the aquifer. The objective of this study was to quantitatively and qualitatively characterize water reserves to provide information and management strategies for the rational use of available water resources in an alluvial aquifer in the Brazilian Northeastern semi-arid region. Shallow and medium-depth wells were analyzed. Water tables were monitored in the dry and wet seasons to calculate water reserves. Groundwater samples were collected for the determination of water quality for irrigation purposes. The increase in agricultural activities is jeopardizing the sustainability of the aquifer’s water, as reserves are not sufficient to meet this demand. Groundwater quality is not limiting for agricultural use. Converting surface irrigation into localized methods will potentially increase water productivity and consequently the irrigated area. This study provides data and makes it possible to recommend appropriate strategies for the exploitation of groundwater resources for the maintenance of agricultural activities under semi-arid conditions, and to avoid overexploitation.

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A practical surface irrigation design based on fuzzy logic and meta-heuristic algorithms

Cited by 11 publications

References 32 publications

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

Determining Tilapia Quality Using the Fuzzy Logic

Groundwater resources for agricultural purposes in the Brazilian semi-arid region

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