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)

Citations

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Working papers

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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. Daxini, Rajiv & Wu, Yupeng, 2024. "Review of methods to account for the solar spectral influence on photovoltaic device performance," Energy, Elsevier, vol. 286(C).
   3. 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).
   4. 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.
   5. 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).
   6. Jiang, Meng & Ding, Kun & Chen, Xiang & Cui, Liu & Zhang, Jingwei & Cang, Yi & Yang, Hang & Gao, Ruiguang, 2024. "CGH-GTO method for model parameter identification based on improved grey wolf optimizer, honey badger algorithm, and gorilla troops optimizer," Energy, Elsevier, vol. 296(C).
   7. 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.
   8. 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).
   9. 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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