Deep-Learning-Based Adaptive Model for Solar Forecasting Using Clustering

Autor: Sourav Malakar, Saptarsi Goswami, Bhaswati Ganguli, Amlan Chakrabarti, Sugata Sen Roy, K. Boopathi, A. G. Rangaraj

Publikováno v: Energies, Vol 15, Iss 10, p 3568 (2022)

Accurate short-term solar forecasting is challenging due to weather uncertainties associated with cloud movements. Typically, a solar station comprises a single prediction model irrespective of time and cloud condition, which often results in subopti

Externí odkaz: https://doaj.org/article/1f3092adb519407eaf7735f572eb45e0

A Novel Feature Representation for Prediction of Global Horizontal Irradiance Using a Bidirectional Model

Autor: Sugata Sen Roy, Bhaswati Ganguli, K. Boopathi, A. G. Rangaraj, Sourav Malakar, Amlan Chakrabarti, Saptarsi Goswami

Publikováno v: Machine Learning and Knowledge Extraction, Vol 3, Iss 47, Pp 946-965 (2021)
Machine Learning and Knowledge Extraction; Volume 3; Issue 4; Pages: 946-965

Complex weather conditions—in particular clouds—leads to uncertainty in photovoltaic (PV) systems, which makes solar energy prediction very difficult. Currently, in the renewable energy domain, deep-learning-based sequence models have reported be

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b92537cd75c8b5138a1c83eaac728ddc
https://www.mdpi.com/2504-4990/3/4/47

Designing a long short-term network for short-term forecasting of global horizontal irradiance

Autor: Sourav Malakar, Saptarsi Goswami, Sugata Sen Roy, K. Boopathi, A. G. Rangaraj, Bhaswati Ganguli, Amlan Chakrabarti

Publikováno v: SN Applied Sciences. 3

Long short-term memory (LSTM) models based on specialized deep neural network-based architecture have emerged as an important model for forecasting time-series. However, the literature does not provide clear guidelines for design choices, which affec

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::75a1be5fdeec644ee114cf68f26fb9b7
https://doi.org/10.1007/s42452-021-04421-x

An Empirical Analysis of Classifiers Using Ensemble Techniques

Autor: Saptarsi Goswami, Reshu Parsuramka, Sourav Malakar, Sanjay Chakraborty

Publikováno v: Data Management, Analytics and Innovation ISBN: 9789811556159

Ensemble methods are algorithms that combine various models together to give higher accuracy than individual models. The ensemble methods used here are majority voting, XGBoost, and random forest. Several decision trees are combined using voting clas

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::47075ccc889fa4e959977027464d5513
https://doi.org/10.1007/978-981-15-5616-6_20

An Online Trend Detection Strategy for Twitter Using Mann–Kendall Non-parametric Test

Autor: Saptarsi Goswami, Sourav Malakar, Amlan Chakrabarti

Publikováno v: Lecture Notes in Networks and Systems ISBN: 9789811039522

Twitter is one of the most popular online social networking and micro-blogging service that enables its users to post and share text-based messages called Tweets. The data generated daily in terms of tweets are enormous and represents a rich source o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0ad275213f65c991174c7e9e8ed08c2a
https://doi.org/10.1007/978-981-10-3953-9_18