Citations Report

Global Journal of Technology and Optimization : Citations & Metrics Report

Articles published in Global Journal of Technology and Optimization have been cited by esteemed scholars and scientists all around the world.

Global Journal of Technology and Optimization has got h-index 12, which means every article in Global Journal of Technology and Optimization has got 12 average citations.

Following are the list of articles that have cited the articles published in Global Journal of Technology and Optimization.

	2022	2021	2020	2019	2018
Year wise published articles	46	43	2	1	9
Year wise citations received	69	80	70	89	106

Journal total citations count	664
Journal impact factor	1.5
Journal 5 years impact factor	2.48
Journal cite score	1.95
Journal h-index	12
Journal h-index since 2018	10

Important citations

Walid MA, Ahmed SM, Sadique SS. A Comparative Analysis of Machine Learning Models for Prediction of Passing Bachelor Admission Test in Life-Science Faculty of a Public University in Bangladesh. In2020 IEEE Electric Power and Energy Conference (EPEC) 2020 Nov 9 (pp. 1-6). IEEE. View at Publisher View at Google Scholar View at Indexing
Zhanga P, Fonnesbeckb C, Schmidtc DC, Whitec J, Mulvaneyd SA. Understanding Barriers to Diabetes Self-Management Using Momentary Assessment and Machine Learning. View at Publisher View at Google Scholar View at Indexing
Kunakorntum I, Hinthong W, Phunchongharn P. A Synthetic Minority Based on Probabilistic Distribution (SyMProD) Oversampling for Imbalanced Datasets. IEEE Access. 2020 Jun 18;8:114692-704. View at Publisher View at Google Scholar View at Indexing
Reddy LC. Machine Learning Prediction of Primary Tissue Origin of Cancer from Gene Expression Read Counts (Doctoral dissertation, University of Nevada, Las Vegas). View at Publisher View at Google Scholar View at Indexing
Zhang P, Fonnesbeck C, Schmidt DC, White J, Mulvaney SA. Understanding Barriers to Self-Management Behavior in Adolescents with Type 1 Diabetes. architecture (LFA). 2018 May;2. View at Publisher View at Google Scholar View at Indexing
Kabir MF. Extracting Useful Information and Building Predictive Models from Medical and Health-care Data Using Machine Learning Techniques (Doctoral dissertation, North Dakota State University). View at Publisher View at Google Scholar View at Indexing
Mujeeb S, Javaid N, Ahmed A, Gulfam SM, Qasim U, Shafiq M, Choi JG. Electricity Theft Detection With Automatic Labeling and Enhanced RUSBoost Classification Using Differential Evolution and Jaya Algorithm. IEEE Access. 2021 Aug 5;9:128521-39. View at Publisher View at Google Scholar View at Indexing
Ozmen E, Cogun F, Alp YK, Altiparmak F. Error Correction Output Code-Based Radar Platform Motion Type Classification. In2021 IEEE Radar Conference (RadarConf21) 2021 May 7 (pp. 1-6). IEEE. View at Publisher View at Google Scholar View at Indexing
Chintham Reddy L. Machine Learning Prediction of Primary Tissue Origin of Cancer from Gene Expression Read Counts. View at Publisher View at Google Scholar View at Indexing
Chaurasia AK. Cluster-based Classification to Process Imbalanced Data using SMOTE Technique. View at Publisher View at Google Scholar View at Indexing
Arif A. Employing Machine Learning and Deep Learning Models for Electricity Theft Detection in Smart Grids. View at Publisher View at Google Scholar View at Indexing
Zhang P. Architectures and Patterns for Moving Towards the Use of High-Frequency, Low-Fidelity Data in Healthcare. Vanderbilt University; 2018. View at Publisher View at Google Scholar View at Indexing
Lamari M, Azizi N, Hammami NE, Boukhamla A, Cheriguene S, Dendani N, Benzebouchi NE. SMOTE–ENN-Based Data Sampling and Improved Dynamic Ensemble Selection for Imbalanced Medical Data Classification. InAdvances on Smart and Soft Computing 2021 (pp. 37-49). Springer, Singapore. View at Publisher View at Google Scholar View at Indexing
Arif A, Alghamdi TA, Khan ZA, Javaid N. Towards Efficient Energy Utilization Using Big Data Analytics in Smart Cities for Electricity Theft Detection. Big Data Research. 2021 Nov 9:100285. View at Publisher View at Google Scholar View at Indexing
Mduma N, Machuve D. Machine Learning Model for Predicting Student Dropout: A Case of Tanzania, Kenya and Uganda. In2021 IEEE AFRICON 2021 Sep 13 (pp. 1-6). IEEE. View at Publisher View at Google Scholar View at Indexing
Gupta R, Asgari H, Azimi G, Rahimi A, Jin X. Analysis of Fatal Truck-Involved Work Zone Crashes in Florida: Application of Tree-Based Models. Transportation Research Record. 2021 Aug 13:03611981211033278. View at Publisher View at Google Scholar View at Indexing
Utami E, Oyong I, Raharjo S, Hartanto AD, Adi S. Supervised learning and resampling techniques on DISC personality classification using Twitter information in Bahasa Indonesia. Applied Computing and Informatics. 2021 Sep 7. View at Publisher View at Google Scholar View at Indexing
Nguyen S, Lamere AT, Olinsky A, Quinn J. The Effects of Sampling Methods on Machine Learning Models for Predicting Long-term Length of Stay: A Case Study of Rhode Island Hospitals. International Journal of Rough Sets and Data Analysis (IJRSDA). 2019 Jul 1;6(3):32-48. View at Publisher View at Google Scholar View at Indexing
Filho JA, Monteiro JM, Mattos CL, Nobre JS. A Practical Guide to Support Predictive Tasks in Data Science. View at Publisher View at Google Scholar View at Indexing
Purnajaya AR, Kusuma WA, DEWI MK. Performance Comparison of Data Sampling Techniques to Handle Imbalanced Class on Prediction of Compound-Protein Interaction. Biogenesis: Jurnal Ilmiah Biologi. 2020;8(1):41-8. View at Publisher View at Google Scholar View at Indexing
Prev 1 2 3 4 5 6 7 8 9 10 11 12 13 ... 19 20 Next »

Relevant Topics

Awards & Nominations

50+ Million Readerbase

Journal Highlights

Google Scholar citation report

Citations: 664

Global Journal of Technology and Optimization received 664 citations as per Google Scholar report

Global Journal of Technology and Optimization

Citations Report

Global Journal of Technology and Optimization : Citations & Metrics Report

Important citations

Walid MA, Ahmed SM, Sadique SS. A Comparative Analysis of Machine Learning Models for Prediction of Passing Bachelor Admission Test in Life-Science Faculty of a Public University in Bangladesh. In2020 IEEE Electric Power and Energy Conference (EPEC) 2020 Nov 9 (pp. 1-6). IEEE.

Zhanga P, Fonnesbeckb C, Schmidtc DC, Whitec J, Mulvaneyd SA. Understanding Barriers to Diabetes Self-Management Using Momentary Assessment and Machine Learning.

Kunakorntum I, Hinthong W, Phunchongharn P. A Synthetic Minority Based on Probabilistic Distribution (SyMProD) Oversampling for Imbalanced Datasets. IEEE Access. 2020 Jun 18;8:114692-704.

Reddy LC. Machine Learning Prediction of Primary Tissue Origin of Cancer from Gene Expression Read Counts (Doctoral dissertation, University of Nevada, Las Vegas).

Zhang P, Fonnesbeck C, Schmidt DC, White J, Mulvaney SA. Understanding Barriers to Self-Management Behavior in Adolescents with Type 1 Diabetes. architecture (LFA). 2018 May;2.

Kabir MF. Extracting Useful Information and Building Predictive Models from Medical and Health-care Data Using Machine Learning Techniques (Doctoral dissertation, North Dakota State University).

Mujeeb S, Javaid N, Ahmed A, Gulfam SM, Qasim U, Shafiq M, Choi JG. Electricity Theft Detection With Automatic Labeling and Enhanced RUSBoost Classification Using Differential Evolution and Jaya Algorithm. IEEE Access. 2021 Aug 5;9:128521-39.

Ozmen E, Cogun F, Alp YK, Altiparmak F. Error Correction Output Code-Based Radar Platform Motion Type Classification. In2021 IEEE Radar Conference (RadarConf21) 2021 May 7 (pp. 1-6). IEEE.

Chintham Reddy L. Machine Learning Prediction of Primary Tissue Origin of Cancer from Gene Expression Read Counts.

Chaurasia AK. Cluster-based Classification to Process Imbalanced Data using SMOTE Technique.

Arif A. Employing Machine Learning and Deep Learning Models for Electricity Theft Detection in Smart Grids.

Zhang P. Architectures and Patterns for Moving Towards the Use of High-Frequency, Low-Fidelity Data in Healthcare. Vanderbilt University; 2018.

Lamari M, Azizi N, Hammami NE, Boukhamla A, Cheriguene S, Dendani N, Benzebouchi NE. SMOTE–ENN-Based Data Sampling and Improved Dynamic Ensemble Selection for Imbalanced Medical Data Classification. InAdvances on Smart and Soft Computing 2021 (pp. 37-49). Springer, Singapore.

Arif A, Alghamdi TA, Khan ZA, Javaid N. Towards Efficient Energy Utilization Using Big Data Analytics in Smart Cities for Electricity Theft Detection. Big Data Research. 2021 Nov 9:100285.

Mduma N, Machuve D. Machine Learning Model for Predicting Student Dropout: A Case of Tanzania, Kenya and Uganda. In2021 IEEE AFRICON 2021 Sep 13 (pp. 1-6). IEEE.

Gupta R, Asgari H, Azimi G, Rahimi A, Jin X. Analysis of Fatal Truck-Involved Work Zone Crashes in Florida: Application of Tree-Based Models. Transportation Research Record. 2021 Aug 13:03611981211033278.

Utami E, Oyong I, Raharjo S, Hartanto AD, Adi S. Supervised learning and resampling techniques on DISC personality classification using Twitter information in Bahasa Indonesia. Applied Computing and Informatics. 2021 Sep 7.

Nguyen S, Lamere AT, Olinsky A, Quinn J. The Effects of Sampling Methods on Machine Learning Models for Predicting Long-term Length of Stay: A Case Study of Rhode Island Hospitals. International Journal of Rough Sets and Data Analysis (IJRSDA). 2019 Jul 1;6(3):32-48.

Filho JA, Monteiro JM, Mattos CL, Nobre JS. A Practical Guide to Support Predictive Tasks in Data Science.

Purnajaya AR, Kusuma WA, DEWI MK. Performance Comparison of Data Sampling Techniques to Handle Imbalanced Class on Prediction of Compound-Protein Interaction. Biogenesis: Jurnal Ilmiah Biologi. 2020;8(1):41-8.

Relevant Topics

Awards & Nominations

50+ Million Readerbase

Journal Highlights

Google Scholar citation report

Citations: 664

Global Journal of Technology and Optimization peer review process verified at publons

Indexed In

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