Modeling the initiation of sediment motion under a wide range of flow conditions using a Geno-Mamdani Fuzzy Inference System method

Bizimana, Hussein; Altunkaynak, Abdüsselam

doi:10.1016/j.ijsrc.2020.03.009

Cited by 7 publications

(6 citation statements)

References 67 publications

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“…From a macroperspective, the quality of employment is the di erent degrees of good and bad that all workers in a region, industry, or country react to when they work [5]. In addition, it is believed that decent work covers two levels of employment quality and employment quantity in connotation, the so-called decent work is actually the good or bad level of employment quality, and the production work with high employment quality corresponds to decent work [6]. Some scholars argue that the quality of employment is actually a measure of the comprehensive employment status of workers in the process of completing their employment behavior [7].…”

Section: Literature Reviewmentioning

confidence: 99%

Quality Evaluation of College Employment Based on Fuzzy Comprehensive Evaluation and Immersive Virtual Realization Technology

Luo

2022

Mobile Information Systems

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In order to further understand the employment forms, employment dynamics, and employment competitiveness of college students, this paper puts forward an employment quality evaluation model based on fuzzy comprehensive evaluation and immersive virtual realization technology in combination with the employment needs and environment of college students. Through horizontal and vertical comparison, field research, and employment quality evaluation model, this paper deeply understands the employment level of college students. From the perspective of the evaluation results of the employment-related work of the 2020 college students, the excellent employment rate has reached 86.25%. From the perspective of the employment quality trend of graduates, the graduate employment quality score is 77.08, and the undergraduate and junior college students’ scores are 74.97 and 77.66, respectively. From the perspective of the excellent employment rate, the employment quality evaluation model proposed in this paper is helpful for the employment of college students.

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Section: Literature Reviewmentioning

confidence: 99%

Quality Evaluation of College Employment Based on Fuzzy Comprehensive Evaluation and Immersive Virtual Realization Technology

Luo

2022

Mobile Information Systems

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“…These rules play a crucial role in supporting the Fuzzy Inference System (FIS), which is responsible for evaluating sharp inputs and converting them into fuzzy input values using the Min (Minimum) implication function. The rule base of the Mamdani fuzzy system, with n inputs, m outputs, and k rules, can be represented according to the following Equation (1) [20]:…”

Section: Application Of Implication Functionsmentioning

confidence: 99%

Fuzzy Logic Application for Determining the Feasibility of Nickel Mining in Southeast Sulawesi Province

Agustina,

Abadi

2024

BAREKENG: J. Math. & App.

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This study uses the Mamdani method to assess the feasibility of nickel mining locations in Southeast Sulawesi Province. Despite the crucial role of mining in the Indonesian economy, research on the site feasibility decisions in mining using the Mamdani method still needs to be completed. Therefore, this study addresses this knowledge gap by providing new contributions and effective solutions. The Mamdani method is employed in the various stages of mining activities, particularly in feasibility studies, which are the main focus. Mining feasibility studies involve both technical and non-technical analyses, encompassing aspects such as nickel reserves and environmental impacts. This research seeks to expand the use of the Mamdani method in mining site feasibility decisions, offering sustainable and environmentally responsible solutions. The research results show that North Konawe Regency has very large estimated nickel reserves but has a relatively low environmental impact and is quite far from the port, thus achieving a high location suitability score for mining. On the other hand, Konawe Regency has lower nickel reserves but has quite a large environmental impact, and the distance to the port is quite far, so the location feasibility score is lower. The outcomes of this research are expected to provide new insights, fill knowledge gaps, and serve as a valuable reference for future mining site feasibility decision-making. The translation is accurate, well-structured, and free from plagiarism.

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“…As a result, a novel and evolutionary technique called GENOFIS was used to predict rainfall time series data. This approach is specified as an integration of the optimized Genetic Algorithms (GAs) and Sugeno FIS (Bizimana and Altunkaynak, 2020).…”

Section: Fig 3: Neuro-fuzzy Inference System Structurementioning

confidence: 99%

Assessment of Rainfall and Climate Change Patterns in the City of Kigali via Machine Learning and IPCC Codex Models and their Impact on Heavy Storms

Bizimana,

Altunkaynak,

Kalin

et al. 2023

Preprint

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Rwanda has been negatively affected by a changing climate, exacerbated by human impact on land and water resources. In most parts of the country the rainfall pattern has changed over the last decades resulting in both enhanced flooding and water shortage / scarcity in much of the country, especially in the Capital City of Kigali and peripheries which is the main economic hub of the country with strong links to the East African region. Changes in precipitation have affected agricultural production, hydropower production, and water supplies, and has been a result of increased heavy storms, and flash floods in the city. This study developed a new predictive model rainfall patterns in the City of Kigali (CoK) in the Republic of Rwanda using evolutionary methodologies that apply machine learning techniques of Fuzzy Inference Systems (FIS) trained via Genetic Algorithms, Neuro Network Systems and a comparative Support Vector Machine tool, and assessment downscaled climate change combinations with predicted rainfall patterns. The models were calibrated and validated using measured rainfall data in the City of Kigali from 1991 through 2023. The model results show the developed Geno Fuzzy Inference System (GENOFIS) model performed better than the Adaptive Neuro Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM) models. The Coefficient of Efficiency (CE), and Root Mean Square Error (RMSE) were used as diagnostic measures for model performance evaluation. Models generated with GENOFIS are therefore recommended for rainfall and related prediction pattern in the City of Kigali for climate change adaptation and resilience policy and planning.

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Modeling the initiation of sediment motion under a wide range of flow conditions using a Geno-Mamdani Fuzzy Inference System method

Cited by 7 publications

References 67 publications

Quality Evaluation of College Employment Based on Fuzzy Comprehensive Evaluation and Immersive Virtual Realization Technology

Quality Evaluation of College Employment Based on Fuzzy Comprehensive Evaluation and Immersive Virtual Realization Technology

Fuzzy Logic Application for Determining the Feasibility of Nickel Mining in Southeast Sulawesi Province

Assessment of Rainfall and Climate Change Patterns in the City of Kigali via Machine Learning and IPCC Codex Models and their Impact on Heavy Storms

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