Indoor air quality pollutants predicting approach using unified labelling process-based multi-criteria decision making and machine learning techniques

Baqer, Noor S.; Albahri, A. S.; Mohammed, Hussein A.; Zaidan, A. A.; Amjed, Rula A.; Al-Bakry, Abbas M.; Albahri, O. S.; Alsattar, Hassan A.; Alnoor, Alhamzah; Alamoodi, A. H.; Zaidan, B. B.; Malik, Radosław; Kareem, Z. H.

doi:10.1007/s11235-022-00959-2

Cited by 10 publications

(2 citation statements)

References 80 publications

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“…He et al, [51] in prediction analysis, Pham et al, [52] in land slide vulnerability, Z. He et al, [53] in textile chemical processing, Kadkhodazadeh et al, [54] in climate change , Mustapha et al, [55] in breast cancer screening, Khosravi et al, [56] in flood susceptibility, Z. Wang et al, [57] in chemical engineering , García et al, [58] in credit affairs, Ali et al, [59] in landslide modeling , Pourkhodabakhsh et al, [60] in human resource management, Chowdhury et al, [61] in COVID-19 classification, Baqer et al, [62] in pollutant prediction, Jassim et al, [63] in diagnosis of adult autism, Al-Bawi et al, [64] in gully erosion. In the above mentioned combinations of MCDM and RFA, various decision making methods such as COPRAS, VIKOR, MULTIMOORA are used.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Machine Learning Algorithms and MCDM Techniques in Optimal Ranking of Battery Electric Vehicles

Sudha,

Edwin,

Nivetha

2023

E3S Web of Conf.

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The automobile industries across the world of this present age are streamlining the manufacture of battery electric vehicles (BEV) as a step towards creating pollution free environment. BEVs are used as an alternate strategy to alleviate the carbon emission at global level. As environmental conservation is one of the long standing sustainable 1f ?developmental goals it is the need of the hour to make a paradigm shift from fossil fuels to renewable energy sources, at the same time this also gives rise to a decision-making problem on making optimal choice of the electric vehicles. In this paper a decision making problem based on ten alternative BEVs and eleven criteria is considered from the earlier works of Faith Ecer. The new ranking method of multi-criteria decision making MCRAT(Multiple Criteria Ranking by Alternative Trace) is used together with three different criterion weight computing methods of AHP(Analytical Hierarchy Process) ,CRITIC (CRiteria Importance Through Intercriteria Correlation) & MEREC (MEthod based on the Removal Effects of Criteria). The results obtained are compared and validated using random forest machine learning algorithm. This research work conjoins multi-criteria decision making methods and machine learning algorithms to make optimal decisions on Battery electric vehicles and this integrated approach yields optimal ranking results and it will certainly create new rooms in decision-making approaches in coming days.

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Section: Literature Reviewmentioning

confidence: 99%

Integrated Machine Learning Algorithms and MCDM Techniques in Optimal Ranking of Battery Electric Vehicles

Sudha,

Edwin,

Nivetha

2023

E3S Web of Conf.

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“…In these contexts, machine learning algorithms can be applied to the processed dataset. Other examples can be found in [9] [10]. Then, Generative AI can play a pivotal role in revolutionizing decision-making processes.…”

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confidence: 99%

The Considerations of Trustworthy AI Components in Generative AI; A Letter to Editor

Albahri,

Khaleel,

Habeeb

2023

Applied Data Science and Analysis

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The Effect of Digital Business Strategy on Improving Customer Journey: Evidence from Users of Virtual Reality Platforms

Al-Eabodi,

Zwain

2023

Lecture Notes in Networks and Systems

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Indoor air quality pollutants predicting approach using unified labelling process-based multi-criteria decision making and machine learning techniques

Cited by 10 publications

References 80 publications

Integrated Machine Learning Algorithms and MCDM Techniques in Optimal Ranking of Battery Electric Vehicles

Integrated Machine Learning Algorithms and MCDM Techniques in Optimal Ranking of Battery Electric Vehicles

The Considerations of Trustworthy AI Components in Generative AI; A Letter to Editor

The Effect of Digital Business Strategy on Improving Customer Journey: Evidence from Users of Virtual Reality Platforms

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