| Mixed multivariate EWMA-CUSUM control charts for an improved process monitoring JO Ajadi, M Riaz Communications in Statistics-Theory and Methods 46 (14), 6980-6993, 2017 | 63 | 2017 |
| On increasing the sensitivity of mixed EWMA–CUSUM control charts for location parameter JO Ajadi, M Riaz, K Al-Ghamdi Journal of Applied Statistics 43 (7), 1262-1278, 2016 | 33 | 2016 |
| A review of dispersion control charts for multivariate individual observations JO Ajadi, Z Wang, IM Zwetsloot Quality Engineering 33 (1), 60-75, 2021 | 28 | 2021 |
| Multivariate mixed EWMA-CUSUM control chart for monitoring the process variance-covariance matrix M Riaz, JO Ajadi, T Mahmood, SA Abbasi IEEE Access 7, 100174-100186, 2019 | 20 | 2019 |
| A comparison of EWMA control charts for dispersion based on estimated parameters IM Zwetsloot, JO Ajadi Computers & Industrial Engineering 127, 436-450, 2019 | 20 | 2019 |
| Nonparametric multivariate covariance chart for monitoring individual observations NA Adegoke, JO Ajadi, A Mukherjee, SA Abbasi Computers & Industrial Engineering 167, 108025, 2022 | 10 | 2022 |
| On the multivariate progressive control chart for effective monitoring of covariance matrix JO Ajadi, K Hung, M Riaz, NA Ajadi, T Mahmood Quality and Reliability Engineering International 37 (6), 2724-2737, 2021 | 10 | 2021 |
| A new multivariate CUSUM chart for monitoring of covariance matrix with individual observations under estimated parameter JO Ajadi, A Wong, T Mahmood, K Hung Quality and Reliability Engineering International 38 (2), 834-847, 2022 | 9 | 2022 |
| A new robust multivariate EWMA dispersion control chart for individual observations JO Ajadi, IM Zwetsloot, KL Tsui Mathematics 9 (9), 1038, 2021 | 9 | 2021 |
| New memory-type control charts for monitoring process mean and dispersion J Olawale Ajadi, M Riaz Scientia Iranica 24 (6), 3423-3438, 2017 | 7 | 2017 |
| Generalized new exponentially weighted moving average control charts (NEWMA) for monitoring process dispersion GA Ajibade, JO Ajadi, OJ Kuboye, E Alih International Journal of Quality & Reliability Management, 2023 | 6 | 2023 |
| Should observations be grouped for effective monitoring of multivariate process variability? JO Ajadi, IM Zwetsloot Quality and Reliability Engineering International 36 (3), 1005-1027, 2020 | 6 | 2020 |
| Generalization of time‐varying fast initial response for exponentially weighted moving average control charts GA Ajibade, M Riaz, A Mohammed, JO Kuboye, E Alih, JO Ajadi Quality and Reliability Engineering International 38 (8), 4157-4168, 2022 | 5 | 2022 |
| On the development of EWMA control chart for Inverse Maxwell distribution SY Arafat, MP Hossain, JO Ajadi, M Riaz Journal of Testing and Evaluation 49 (2), 1086-1103, 2021 | 4 | 2021 |
| Modeling Monthly Average Temperature of Dhahran City of Saudi-Arabia Using Arima Models NA Ajadi, JO Ajadi, AS Damisa, OE Asiribo, GA Dawodu Journal of data science 3 (5), 2017 | 2 | 2017 |
| Developing Machine Learning Models for Catalysts in Oxidative Dehydrogenation of n‐butane G Tanimu, J Olawale Ajadi, Y Yahaya, H Alasiri, NA Adegoke ChemCatChem 15 (17), e202300598, 2023 | 1 | 2023 |
| Detecting outliers in the multivariate control charts for dispersion monitoring JO Ajadi, IA Raji, N Abbas, M Riaz Quality and Reliability Engineering International 40 (4), 1904-1917, 2024 | | 2024 |
| Predicting malaria outbreak in The Gambia using machine learning techniques O Khan, JO Ajadi, MP Hossain Plos one 19 (5), e0299386, 2024 | | 2024 |
| Multivariate Technique for Detecting Variations in High-Dimensional Imagery RA Sanusi, JO Ajadi, SA Abbasi, TO Dauda, NA Adegoke IEEE Access, 2024 | | 2024 |
| Control Charts for Process Dispersion in Statistical Process Monitoring JO Ajadi City University of Hong Kong, 2020 | | 2020 |
