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Subseasonal Prediction of Summer Temperature in West Africa Using Artificial Intelligence: A Case Study of Senegal

International journal of intelligent systems, 2024-02, Vol.2024, p.1-19

2024

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The impact of diversity on the accuracy of evidential classifier ensembles

International journal of approximate reasoning, 2012-06, Vol.53 (4), p.584-607

Bi, Yaxin

2012

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Clustering-based ensemble learning for activity recognition in smart homes

Sensors (Basel, Switzerland), 2014-07, Vol.14 (7), p.12285-12304

2014

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The combination of multiple classifiers using an evidential reasoning approach

Artificial intelligence, 2008-10, Vol.172 (15), p.1731-1751

2008

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Aggregated topic models for increasing social media topic coherence

Applied intelligence (Dordrecht, Netherlands), 2020, Vol.50 (1), p.138-156

2020

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Detecting anomalies in sequential data augmented with new features

The Artificial intelligence review, 2020, Vol.53 (1), p.625-652

2020

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On combining classifier mass functions for text categorization

IEEE transactions on knowledge and data engineering, 2005-10, Vol.17 (10), p.1307-1319

2005

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Belief Functions: Theory and Applications: 8th International Conference, BELIEF 2024, Belfast, UK, September 2–4, 2024, Proceedings

2024

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An Effective Combination of Multiple Classifiers for Toxicity Prediction

Fuzzy Systems and Knowledge Discovery, 2006, p.481-490

2006

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Data mining and machine learning approaches for prediction modelling of schistosomiasis disease vectors: Epidemic disease prediction modelling

International journal of machine learning and cybernetics, 2020-06, Vol.11 (6), p.1159-1178

2020

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Data mining and machine learning approaches for prediction modelling of schistosomiasis disease vectors

International journal of machine learning and cybernetics, 2020-06, Vol.11 (6), p.1159-1178

2020

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Combining multiple sets of rules for improving classification via measuring their closenesses

Lecture notes in computer science, 2006, p.1068-1072

2006

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Combining Rules for Text Categorization Using Dempster’s Rule of Combination

Intelligent Data Engineering and Automated Learning – IDEAL 2004, 2004, p.457-463

2004

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Optimization Under Severe Uncertainty: a Generalized Minimax Regret Approach for Problems with Linear Objectives

Belief Functions: Theory and Applications, 2024, p.197-204

2024

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Knowledge Science, Engineering and Management: 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part I

2023

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Knowledge Science, Engineering and Management: 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part II

2023

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Knowledge Science, Engineering and Management: 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part IV

2023

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Knowledge Science, Engineering and Management: 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part III

2023

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An Evidential Time-to-Event Prediction Model Based on Gaussian Random Fuzzy Numbers

Belief Functions: Theory and Applications, 2024, p.49-57

2024

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Uncertainty Quantification in Regression Neural Networks Using Likelihood-Based Belief Functions

Belief Functions: Theory and Applications, 2024, p.40-48

2024

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Combination of Dependent Gaussian Random Fuzzy Numbers

Belief Functions: Theory and Applications, 2024, p.264-272

2024

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Intelligent Systems and Applications: Extended and Selected Results from the SAI Intelligent Systems Conference (IntelliSys) 2016

2017

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A Hybrid Intelligent Approach for Metal-Loss Defect Depth Prediction in Oil and Gas Pipelines

Intelligent Systems and Applications, 2016, Vol.650, p.1-18

2016

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Assembly Assisted by Augmented Reality (A3R)

Intelligent Systems and Applications, 2016, Vol.650, p.281-300

2016

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Predicting Financial Time Series Data Using Hybrid Model

Intelligent Systems and Applications, 2016, Vol.650, p.19-41

2016

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Subseasonal Prediction of Summer Temperature in West Africa Using Artificial Intelligence: A Case Study of Senegal

The impact of diversity on the accuracy of evidential classifier ensembles

Clustering-based ensemble learning for activity recognition in smart homes

The combination of multiple classifiers using an evidential reasoning approach

Aggregated topic models for increasing social media topic coherence

Detecting anomalies in sequential data augmented with new features

On combining classifier mass functions for text categorization

Belief Functions: Theory and Applications: 8th International Conference, BELIEF 2024, Belfast, UK, September 2–4, 2024, Proceedings

An Effective Combination of Multiple Classifiers for Toxicity Prediction

Data mining and machine learning approaches for prediction modelling of schistosomiasis disease vectors: Epidemic disease prediction modelling

Data mining and machine learning approaches for prediction modelling of schistosomiasis disease vectors

Combining multiple sets of rules for improving classification via measuring their closenesses

Combining Rules for Text Categorization Using Dempster’s Rule of Combination

Optimization Under Severe Uncertainty: a Generalized Minimax Regret Approach for Problems with Linear Objectives

Knowledge Science, Engineering and Management: 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part I

Knowledge Science, Engineering and Management: 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part II

Knowledge Science, Engineering and Management: 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part IV

Knowledge Science, Engineering and Management: 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part III

An Evidential Time-to-Event Prediction Model Based on Gaussian Random Fuzzy Numbers

Uncertainty Quantification in Regression Neural Networks Using Likelihood-Based Belief Functions

Combination of Dependent Gaussian Random Fuzzy Numbers

Intelligent Systems and Applications: Extended and Selected Results from the SAI Intelligent Systems Conference (IntelliSys) 2016

A Hybrid Intelligent Approach for Metal-Loss Defect Depth Prediction in Oil and Gas Pipelines

Assembly Assisted by Augmented Reality (A3R)

Predicting Financial Time Series Data Using Hybrid Model

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