Works (5)

Updated: July 5th, 2023 15:41

2020 journal article

Least cost energy system pathways towards 100% renewable energy in Ireland by 2050

ENERGY, 207.

author keywords: 100% Renewable energy; Electrification; Energy system optimization model; Uncertainty analysis
TL;DR: Results show that compared to decarbonization targets, focusing on renewable penetration without considering carbon capture options is significantly more cost effective in carbon mitigation and pathways relying on international bioenergy imports are slightly cheaper and faces less economic and technical challenges. (via Semantic Scholar)
Source: Web Of Science
Added: August 31, 2020

2019 journal article

Building conflict uncertainty into electricity planning: A South Sudan case study

ENERGY FOR SUSTAINABLE DEVELOPMENT, 49, 53–64.

Contributors: N. Patankar n, A. Queiroz*, J. DeCarolis n, M. Bazilian* & D. Chattopadhyay*

author keywords: Stochastic programming; Conflict uncertainty; South Sudan
Sources: Web Of Science, ORCID
Added: April 9, 2019

2017 journal article

Variations of cohort intelligence

SOFT COMPUTING, 22(6), 1731–1747.

By: N. Patankar n & A. Kulkarni*

author keywords: Cohort intelligence; Self-supervised learning; Socio-inspired optimization; Unconstrained test problems
TL;DR: The analysis of variations of cohort intelligence gives very important insight about the strategy that should be followed while working in a cohort and may provide insight into variegated applicability domain of the CI methodology. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2016 journal article

Constraint handling in probability collectives using a modified feasibility-based rule

International Journal of Computational Science and Engineering, 13(4), 303–321.

By: A. Kulkarni*, N. Patankar n & K. Tai*

Source: NC State University Libraries
Added: August 6, 2018

2014 journal article

Multi-criteria probability collectives

INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 6(6), 369–383.

By: N. Patankar n, A. Kulkarni*, K. Tai*, T. Ghate* & A. Parvate

author keywords: multi-criteria probability collectives; MCPCs; multi-agent system; MAS; collective intelligence; COIN; constrained test problems
TL;DR: A variation of the distributed optimisation multi-agent system (MAS) approach of probability collectives (PC) in collective intelligence domain referred to as multi-criteria probability collective (MCPC) is proposed, which is validated by solving a variety of constrained test problems. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

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