Hybrid Ontology-based knowledge with multi-objective optimization model framework for Decision Support System in intercropping

Phoksawat, Kornkanok; Mahmuddin, Massudi

doi:10.25046/aj0203172

Cited by 5 publications

(1 citation statement)

References 27 publications

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“…From the process above, it can be seen that creating a network is the first step and it is the most important component in solving the problem. [6][7][8][9][10]. ANP also has disadvantages in terms of network construction which is not clear because when starting an incorrect network, it will affect the decision in choosing the best alternative.…”

Section: Introductionmentioning

confidence: 99%

Network Modeling with ANP to Determine the Appropriate Area for the Development of Dry Port in Thailand

Sukmanee¹,

Kesvarakul²,

Janthong³

2020

Adv. sci. technol. eng. syst. j.

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One drawback of the Multiple Criteria Decision Making (MCDM) problem with the Analytic Network Process (ANP) is that the origin of the network cannot be clearly defined. In addition, it is not possible to specify internal relationship between criteria and subcriteria. The application of Design Structure Matrix (DSM) with the Partitioning Reachability Matrix method resulted in a clear understanding of the network's origin and was able to identify the relationship of all criteria in the system. Then, the data were analyzed by the ANP process using Super Decision Program. This will result in more reliable outcomes for selecting the best alternative with higher accuracy. This case study determined the suitable area for dry port development in 5 provinces in Thailand. Based on the analysis process mentioned above, Nakhon Ratchasima is the most suitable area to build a dry port of Thailand.

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Section: Introductionmentioning

confidence: 99%

Network Modeling with ANP to Determine the Appropriate Area for the Development of Dry Port in Thailand

Sukmanee¹,

Kesvarakul²,

Janthong³

2020

Adv. sci. technol. eng. syst. j.

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Development of Paddy Transplanter Machine Using Low-Cost Materials

Waghmare,

Shelare,

Mungle

et al. 2024

Lecture Notes in Mechanical Engineering

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Meta-Heuristic Feature Optimization for ontology-based data security in a campus workplace with robotic assistance

Gong¹,

Samuel

Pandian

2021

WOR

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BACKGROUND: For campus workplace secure text mining, robotic assistance with feature optimization is essential. The space model of the vector is usually used to represent texts. Besides, there are still two drawbacks to this basic approach: the curse and lack of semantic knowledge. OBJECTIVES: This paper proposes a new Meta-Heuristic Feature Optimization (MHFO) method for data security in the campus workplace with robotic assistance. Firstly, the terms of the space vector model have been mapped to the concepts of data protection ontology, which statistically calculate conceptual frequency weights by term various weights. Furthermore, according to the designs of data protection ontology, the weight of theoretical identification is allocated. The dimensionality of functional areas is reduced significantly by combining standard frequency weights and weights based on data protection ontology. In addition, semantic knowledge is integrated into this process. RESULTS: The results show that the development of the characteristics of this process significantly improves campus workplace secure text mining. CONCLUSION: The experimental results show that the development of the features of the concept hierarchy structure process significantly enhances data security of campus workplace text mining with robotic assistance.

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Hybrid Ontology-based knowledge with multi-objective optimization model framework for Decision Support System in intercropping

Cited by 5 publications

References 27 publications

Network Modeling with ANP to Determine the Appropriate Area for the Development of Dry Port in Thailand

Network Modeling with ANP to Determine the Appropriate Area for the Development of Dry Port in Thailand

Development of Paddy Transplanter Machine Using Low-Cost Materials

Meta-Heuristic Feature Optimization for ontology-based data security in a campus workplace with robotic assistance

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