Work place: Galgotias College of Engineering and Technology /HOD (Computer Science), Gr.Noida, 201310, India
Research Interests: Computer systems and computational processes, Data Mining, Data Structures and Algorithms, Logic Calculi, Logic Circuit Theory
Bhawna Mallick is Professor and Head of the Department since 2009. She has experience of more than 17 years in teaching,research,software development, technical evangelizing, consultation and administration. She is also the Dean (Academics) since January 2015. She has done her B.E (Computer Technology) from Nagpur University, M.Tech. from Punjabi University, Patiala and Ph.D from Thapar University, Patiala. Her research work is both in Data mining and Fuzzy logic giving new algorithms to generate useful patterns that are of interest for practical applications. She has given more than 30 publications in reputed International journal and conference mostly based on sequential pattern mining, incremental mining and distributed data mining. Six research papers are published/accepted in Science Citation Indexed journals with good impact factors and publishers like Taylor and Francis, Atlantis Press.
She has worked with industries like Infosys Technologies Limited, NIIT Technologies Limited. She has good understanding of emerging technologies, experience in designing multi-tier enterprise solutions using J2EE technologies and standards, developing business solutions using Oracle/Developer 2000. She has taught various courses at undergraduate and postgraduate level to engineering students. Dr Mallick has supervised more than 25 M.Tech. thesis work for Mahamaya Technical University, Gautam Buddh Technical University and Uttar Pradesh Technical University. She is on editorial/review panel for International journals and conferences. She has been organizing chair and general chair for International conferences technically sponsored by IEEE and International Neural Network society.
DOI: https://doi.org/10.5815/ijmecs.2017.04.07, Pub. Date: 8 Apr. 2017
The aim of the study is to introduce some appropriate approaches which might help in improving the efficiency of weather’s parameters. Weather is a natural phenomenon for which forecasting is a great challenge today. Weather parameters such as Rainfall, Relative Humidity , Wind Speed , Air Temperature are highly non-linear and complex phenomena, which include statistical simulation and modeling for its correct forecasting. Weather Forecasting is used to simplify the purpose of knowledge and tools which are used for the state of atmosphere at a given place. The expectations are becoming more complicated due to changing weather state. There are different software and their types are available for Time Series forecasting. Our aim is to analyze the parameter and do the comparison of some strategies in predicting these temperatures. Here we tend to analyze the data of given parameters and to notice their predictions for a particular period by using the strategy of Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing (ETS) .The data from meteorological centers has been taken for the comparison of methods using packages such as ggplot2, forecast, time Date in R and automatic prediction strategies which are available within the package applied for modeling with ARIMA and ETS methods. On the basis of accuracy we tend to attempt the simplest methodology and then we will compare our model on the basis of MAE, MASE, MAPE and RMSE. An identification of model will be the chromatic checkup of both the ACF and PACF to hypothesize many probable models which are going to be projected by selection criteria i.e. AIC, AICc and BIC.[...] Read more.
Subscribe to receive issue release notifications and newsletters from MECS Press journals