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Manjeevan Seera

Personal Details

First Name:Manjeevan
Middle Name:
Last Name:Seera
Suffix:
RePEc Short-ID:pse728
[This author has chosen not to make the email address public]

Affiliation

School of Business
Monash University

Sunway, Malaysia
https://www.monash.edu.my/business
RePEc:edi:sbmonmy (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Manjeevan Seera & Chee Peng Lim & Ajay Kumar & Lalitha Dhamotharan & Kim Hua Tan, 2024. "An intelligent payment card fraud detection system," Post-Print hal-04514342, HAL.

Articles

  1. Manjeevan Seera & Chee Peng Lim & Ajay Kumar & Lalitha Dhamotharan & Kim Hua Tan, 2024. "An intelligent payment card fraud detection system," Annals of Operations Research, Springer, vol. 334(1), pages 445-467, March.
  2. Asoke K Nandi & Kuldeep Kaur Randhawa & Hong Siang Chua & Manjeevan Seera & Chee Peng Lim, 2022. "Credit card fraud detection using a hierarchical behavior-knowledge space model," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-16, January.
  3. Seera, Manjeevan & Tan, Choo Jun & Chong, Kok-Keong & Lim, Chee Peng, 2021. "Performance analyses of various commercial photovoltaic modules based on local spectral irradiances in Malaysia using genetic algorithm," Energy, Elsevier, vol. 223(C).
  4. Manjeevan Seera & Chee Peng Lim & Chu Kiong Loo, 2016. "Motor fault detection and diagnosis using a hybrid FMM-CART model with online learning," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1273-1285, December.
  5. Manjeevan Seera & Chee Peng Lim & Dahaman Ishak, 2012. "Detection and Diagnosis of Broken Rotor Bars in Induction Motors Using the Fuzzy Min-Max Neural Network," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 3(1), pages 44-55, January.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

    Sorry, no citations of working papers recorded.

Articles

  1. Seera, Manjeevan & Tan, Choo Jun & Chong, Kok-Keong & Lim, Chee Peng, 2021. "Performance analyses of various commercial photovoltaic modules based on local spectral irradiances in Malaysia using genetic algorithm," Energy, Elsevier, vol. 223(C).

    Cited by:

    1. Daxini, Rajiv & Wilson, Robin & Wu, Yupeng, 2023. "Modelling the spectral influence on photovoltaic device performance using the average photon energy and the depth of a water absorption band for improved forecasting," Energy, Elsevier, vol. 284(C).
    2. Peng, Cheng & Chen, Heng & Lin, Chaoran & Guo, Shuang & Yang, Zhi & Chen, Ke, 2021. "A framework for evaluating energy security in China: Empirical analysis of forecasting and assessment based on energy consumption," Energy, Elsevier, vol. 234(C).
    3. Sammy J. Martínez-Deusa & Carlos A. Gómez-García & Jaime Velasco-Medina, 2023. "A Platform for Outdoor Real-Time Characterization of Photovoltaic Technologies," Energies, MDPI, vol. 16(6), pages 1-16, March.
    4. Siyu, Liu & Kangwen, Sun & Jian, Gao & Haoquan, Liang, 2023. "Receiving energy analysis and optimal design of crystalline silicon solar cell array on solar airship," Energy, Elsevier, vol. 282(C).
    5. Wilson Castillo-Rojas & Fernando Medina Quispe & César Hernández, 2023. "Photovoltaic Energy Forecast Using Weather Data through a Hybrid Model of Recurrent and Shallow Neural Networks," Energies, MDPI, vol. 16(13), pages 1-25, July.
    6. Belsky, A.A. & Glukhanich, D.Y. & Carrizosa, M.J. & Starshaia, V.V., 2022. "Analysis of specifications of solar photovoltaic panels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    7. Md. Imamul Islam & Mohd Shawal Jadin & Ahmed Al Mansur & Nor Azwan Mohamed Kamari & Taskin Jamal & Molla Shahadat Hossain Lipu & Mohd Nurulakla Mohd Azlan & Mahidur R. Sarker & A. S. M. Shihavuddin, 2023. "Techno-Economic and Carbon Emission Assessment of a Large-Scale Floating Solar PV System for Sustainable Energy Generation in Support of Malaysia’s Renewable Energy Roadmap," Energies, MDPI, vol. 16(10), pages 1-32, May.

  2. Manjeevan Seera & Chee Peng Lim & Chu Kiong Loo, 2016. "Motor fault detection and diagnosis using a hybrid FMM-CART model with online learning," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1273-1285, December.

    Cited by:

    1. Sangho Lee & Youngdoo Son, 2021. "Motor Load Balancing with Roll Force Prediction for a Cold-Rolling Setup with Neural Networks," Mathematics, MDPI, vol. 9(12), pages 1-21, June.
    2. Jungwon Yu & Jaeyel Jang & Jaeyeong Yoo & June Ho Park & Sungshin Kim, 2018. "A Fault Isolation Method via Classification and Regression Tree-Based Variable Ranking for Drum-Type Steam Boiler in Thermal Power Plant," Energies, MDPI, vol. 11(5), pages 1-19, May.
    3. Dawid Szurgacz & Sergey Zhironkin & Michal Cehlár & Stefan Vöth & Sam Spearing & Ma Liqiang, 2021. "A Step-by-Step Procedure for Tests and Assessment of the Automatic Operation of a Powered Roof Support," Energies, MDPI, vol. 14(3), pages 1-16, January.
    4. Maroua Said & Khaoula ben Abdellafou & Okba Taouali, 2020. "Machine learning technique for data-driven fault detection of nonlinear processes," Journal of Intelligent Manufacturing, Springer, vol. 31(4), pages 865-884, April.
    5. Mengting Yao & Yun Zhu & Junjie Li & Hua Wei & Penghui He, 2019. "Research on Predicting Line Loss Rate in Low Voltage Distribution Network Based on Gradient Boosting Decision Tree," Energies, MDPI, vol. 12(13), pages 1-14, June.
    6. Gang Wang & Feng Zhang & Bayi Cheng & Fang Fang, 2021. "DAMER: a novel diagnosis aggregation method with evidential reasoning rule for bearing fault diagnosis," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 1-20, January.
    7. Xiang Li & Wei Zhang & Qian Ding & Jian-Qiao Sun, 2020. "Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 433-452, February.
    8. Seokho Kang, 2020. "Joint modeling of classification and regression for improving faulty wafer detection in semiconductor manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 319-326, February.
    9. Yang Hui & Xuesong Mei & Gedong Jiang & Fei Zhao & Pengcheng Shen, 2020. "Assembly consistency improvement of straightness error of the linear axis based on the consistency degree and GA-MSVM-I-KM," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1429-1441, August.

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