Institution
Jadavpur University
Education•Kolkata, India•
About: Jadavpur University is a education organization based out in Kolkata, India. It is known for research contribution in the topics: Population & Fuzzy logic. The organization has 10856 authors who have published 27678 publications receiving 422069 citations. The organization is also known as: JU & Jadabpur University.
Papers published on a yearly basis
Papers
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TL;DR: Carbon quantum dots (CQDs) as discussed by the authors are a new class of fluorescence small carbon nanoparticles with a particle size of less than 10nm and have vast applications in the field of bioimaging, biosensing and disease-detection.
431 citations
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TL;DR: In this article, the authors present a comprehensive literature review of the latest research and development in the field of microgrid as a promising power system, which shows a broad overview on the worldwide research trend on microgrid which is most significant topic at present.
Abstract: The concept of integration of distributed energy resources for formation of microgrid will be most significant in near future. The latest research and development in the field of microgrid as a promising power system through a comprehensive literature review is presented in this paper. It shows a broad overview on the worldwide research trend on microgrid which is most significant topic at present. This literature survey reveals that integration of distributed energy resources, operation, control, power quality issues and stability of microgrid system should be explored to implement microgrid successfully in real power scenario.
431 citations
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01 Jan 2008TL;DR: This chapter provides two recent algorithms for evolutionary optimization – well known as particle swarm optimization (PSO) and differential evolution (DE), inspired by biological and sociological motivations and can take care of optimality on rough, discontinuous and multimodal surfaces.
Abstract: Since the beginning of the nineteenth century, a significant evolution in optimization theory has been noticed. Classical linear programming and traditional non-linear optimization techniques such as Lagrange’s Multiplier, Bellman’s principle and Pontyagrin’s principle were prevalent until this century. Unfortunately, these derivative based optimization techniques can no longer be used to determine the optima on rough non-linear surfaces. One solution to this problem has already been put forward by the evolutionary algorithms research community. Genetic algorithm (GA), enunciated by Holland, is one such popular algorithm. This chapter provides two recent algorithms for evolutionary optimization – well known as particle swarm optimization (PSO) and differential evolution (DE). The algorithms are inspired by biological and sociological motivations and can take care of optimality on rough, discontinuous and multimodal surfaces. The chapter explores several schemes for controlling the convergence behaviors of PSO and DE by a judicious selection of their parameters. Special emphasis is given on the hybridizations of PSO and DE algorithms with other soft computing tools. The article finally discusses the mutual synergy of PSO with DE leading to a more powerful global search algorithm and its practical applications.
426 citations
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01 Jan 2009TL;DR: This chapter presents a new adaptive variant of BFOA, where the chemotactic step size is adjusted on the run according to the current fitness of a virtual bacterium, and discusses the hybridization of B FOA with other optimization techniques.
Abstract: Bacterial foraging optimization algorithm (BFOA) has been widely accepted as a global optimization algorithm of current interest for distributed optimization and control BFOA is inspired by the social foraging behavior of Escherichia coli BFOA has already drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains The underlying biology behind the foraging strategy of Ecoli is emulated in an extraordinary manner and used as a simple optimization algorithm This chapter starts with a lucid outline of the classical BFOA It then analyses the dynamics of the simulated chemotaxis step in BFOA with the help of a simple mathematical model Taking a cue from the analysis, it presents a new adaptive variant of BFOA, where the chemotactic step size is adjusted on the run according to the current fitness of a virtual bacterium Nest, an analysis of the dynamics of reproduction operator in BFOA is also discussed The chapter discusses the hybridization of BFOA with other optimization techniques and also provides an account of most of the significant applications of BFOA until date
421 citations
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TL;DR: Limited trials of 4 arsenic chelators in the treatment of chronic arsenic toxicity in West Bengal over the last 2 decades do not provide any clinical, biochemical, or histopathological benefit except for the accompanying preliminary report of clinical benefit with dimercaptopropanesulfonate therapy.
Abstract: Fifty districts of Bangladesh and 9 districts in West Bengal, India have arsenic levels in groundwater above the World Health Organization's maximum permissible limit of 50 μg/L. The area and popul...
416 citations
Authors
Showing all 10999 results
Name | H-index | Papers | Citations |
---|---|---|---|
Subir Sarkar | 149 | 1542 | 144614 |
Amartya Sen | 149 | 689 | 141907 |
Susumu Kitagawa | 125 | 809 | 69594 |
Praveen Kumar | 88 | 1339 | 35718 |
Rodolphe Clérac | 78 | 506 | 22604 |
Rajesh Gupta | 78 | 936 | 24158 |
Santanu Bhattacharya | 67 | 400 | 14039 |
Swagatam Das | 64 | 370 | 19153 |
Anupam Bishayee | 62 | 237 | 11589 |
Michael G. B. Drew | 61 | 1315 | 24747 |
Soujanya Poria | 57 | 175 | 13352 |
Madeleine Helliwell | 54 | 370 | 9898 |
Tapas Kumar Maji | 54 | 253 | 9804 |
Pulok K. Mukherjee | 54 | 296 | 10873 |
Dipankar Chakraborti | 54 | 115 | 12078 |