P
Palash Kumar Kundu
Researcher at Jadavpur University
Publications - 61
Citations - 386
Palash Kumar Kundu is an academic researcher from Jadavpur University. The author has contributed to research in topics: Computer science & Fault (power engineering). The author has an hindex of 8, co-authored 42 publications receiving 196 citations. Previous affiliations of Palash Kumar Kundu include Bangladesh Rice Research Institute & Bangladesh Agricultural University.
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Transmission Line Faults in Power System and the Different Algorithms for Identification, Classification and Localization: A Brief Review of Methods
TL;DR: The importance of having a robust fault identification, classification and localization algorithm which would be successfully able to drive as well as actuate the digital relaying system is laid down.
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Electronic Tongue System for Water Sample Authentication: A Slantlet-Transform-Based Approach
TL;DR: The proposed system hybridizes ST with two variants of backpropagation-neural-network-based binary classifiers to develop an automated authentication tool showed encouraging average authentication percentage accuracy, on the order of over 80% for most water categories and even producing accuracy results exceeding 90%, for several categories.
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Classification and authentication of unknown water samples using machine learning algorithms.
TL;DR: A PCA (principal component analysis) based classification and authentication tool was developed in this study as the machine learning component of the E-tongue system.
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Optimal Fractional Order IMC-Based Series Cascade Control Strategy with Dead-Time Compensator for Unstable Processes
TL;DR: This work proposes an advanced dead-time compensator-based series cascade control structure (SCCS) for unstable processes that has three controllers (named as primary, secondary and stabilizing controllers) and uses fractional order-based internal model control (IMC) approach.
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Prototype Model Design of Automatic Irrigation Controller
TL;DR: A fuzzy rule-base irrigation controller prototype that can the irrigation scheduling for all types of crops, across all climatic conditions for all soil types upon feeding the proper soil–crop–growth stage combinations in the inference engine.