Assistant Professor

Dr Priyanka Singh

Department of Computer Science and Engineering

Interests

  1. Soft Computing
  2. Optimization
  3. Time series prediction

Faculty Details

Education

2012

Ideal Institute of Technology, Ghaziabad, Uttar Pradesh
India
BTech

2015

Indian Institute of Information Technology Allahabad, Prayagraj, Uttar Pradesh
India
MTech

2020

Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh
India
PhD

Experience

  • August 2019 – Assistant Professor – VIT Bhopal University, Bhopal

Research Interest

  • Optimization of real engineering problems using meta-heuristic algorithms.
  • Development of accurate and stable models to time series problems such as electricity load and price forecasting on very short-term, short-term and long term basis.
  • Machine learning approach to classification of microarray data.

Awards & Fellowships

  • 2012 & 2013 – GATE

Publications

Journals

  • Priyanka Singh, and Pragya Dwivedi. "Integration of new evolutionary approach with artificial neural network for solving short term load forecast problem." Applied Energy (2018), 217: 537-549.
  • Priyanka Singh, Pragya Dwivedi, and Vibhor Kant. "A hybrid method based on neural network and improved environmental adaptation method using Controlled Gaussian Mutation with real parameter for short-term load forecasting." Energy (2019), 174: 460-477.
  • Priyanka Singh, and Pragya Dwivedi. "A Novel Hybrid Model Based on Neural Network and Multi-Objective Optimization for Effective Load Forecast." Energy (2019), 182: 606-622.
  • Priyanka Singh and Rahul Kottath, "A Comparative Analysis of Hybrid Optimization Algorithms for Solving Constrained Engineering Problems." Computers & Industrial Engineering (2021), 162: 107739.
  • Priyanka Singh, Rahul Kottath and G. Tejani, "Ameliorated Follow The Leader: Algorithm and Application to Truss Design Problem" Structure (2022), Vol. 42, pp. 181-204.
  • Priyanka Singh, and Rahul Kottath, "Chaos follow the leader algorithm: Application to data classification." Journal of Computational Science 65 (2022): 101886.
  • Priyanka Singh, and Rahul Kottath, "Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices." Utilities Policy 79 (2022): 101444.
  • Rahul Kottath, and Priyanka Singh, "Improved Follow the Leader (iFTL): a Swarm-Based Approach and its Application to Short-Term Electricity Price Forecasting", Energy 263 (2023): 125641.

Conference Papers

  • Priyanka Singh, K.K. Mishra and Pragya Dwivedi, "Enhanced hybrid model for electricity load forecast through artificial neural network and Jaya algorithm." 115-120. 10.1109/ICCONS.2017.8250660
  • Priyanka Singh, and Pragya Dwivedi, "Short-Term Electricity Load Forecast Using Hybrid Model Based on Neural Network and Evolutionary Algorithm." Numerical Optimization in Engineering and Sciences. Springer, Singapore, 2020. 167-176.
  • Priyanka Singh and Rahul Kottath. "Application of Mutation Operators on Grey Wolf Optimizer." 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2021.
  • Priyanka Singh, and Pragya Dwivedi, "Very Short-Term Load Forecasting with Hybrid Deep Learning Neural Network in Delhi, India." (Published in Soft Computing: Theories and Applications (SoCTA), 2021)
  • Rahul kottath, and Priyanka Singh, "A Meta-heuristic Learning Approach for Short-term Price forecasting." (Published in Soft Computing: Theories and Applications (SoCTA), 2021)

Contact Details

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