Applying fuzzy analytic hierarchy process to select models developed by abstraction and decision fusion architecture (case study: classification of Persian handwritten characters)
Purpose: This research presents an application-oriented approach for developing machine learning models that consider the trade-off between model accuracy, processing speed, and efficient resource utilization, focusing on applications such as wearable smart systems.Methodology: A set of models is de...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | fas |
| Published: |
Ayandegan Institute of Higher Education, Tonekabon,
2024-11-01
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| Series: | تصمیم گیری و تحقیق در عملیات |
| Subjects: | |
| Online Access: | https://www.journal-dmor.ir/article_211082_f5e82d90e98bd8633aec8e7447c8e9d7.pdf |
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| Summary: | Purpose: This research presents an application-oriented approach for developing machine learning models that consider the trade-off between model accuracy, processing speed, and efficient resource utilization, focusing on applications such as wearable smart systems.Methodology: A set of models is developed based on the Abstraction and Decision Fusion Architecture (ADFA), and then, using a multi-criteria decision-making approach, the appropriate models for the intended application are identified. The proposed methodology has three main phases: 1) developing models based on the ADFA, 2) defining evaluation criteria, and 3) selecting models using the Fuzzy Analytic Hierarchy Process (FAHP).Findings: The experimental results of this research demonstrate the effectiveness of this approach in developing suitable machine learning models for applications related to wearable devices, such as smart glasses.Originality/Value: This research introduces three innovations: 1) the use of ADFA for developing models for the classification of Persian handwritten characters, 2) defining a new abstraction for summarizing handwritten character images, and 3) developing a fuzzy multi-criteria decision-making approach for mapping the developed models in the ADFA to real-world applications. |
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| ISSN: | 2538-5097 2676-6159 |