Thapar University

About: Thapar University is a education organization based out in Patiāla, Punjab, India. It is known for research contribution in the topics: Computer science & Cloud computing. The organization has 2944 authors who have published 8558 publications receiving 130392 citations.

Online Handwritten Gurmukhi Character Recognition Using Elastic Matching

Abstract: This paper presents implementation of elastic matching technique to recognize online handwritten Gurmukhi characters. We have discussed a process that recognizes characters in two stages. First stage recognizes the strokes, in second stage, character is evaluated on the basis of recognized strokes. Feature are computed to strengthen recognition results. Also, we have discussed a simple way to store data for handwritten strokes and characters. The database for strokes stores script number, stroke number and stroke sample number for every point of a stroke. For 60 writer's and a set of 41 Gurmukhi characters, we have obtained recognition rate as 90.08%.

Generalized intuitionistic fuzzy soft power aggregation operator based on t-norm and their application in multicriteria decision-making

Abstract: The aim of this paper is to develop some new power aggregation operators for intuitionistic fuzzy (IF) soft numbers. The aggregation operators are named as IF soft power averaging (IFSPA) operator, weighted IFSPA (WIFSPA) operator, ordered WIFSPA operator, IF soft power geometric (IFSPG) operator, and weighted and ordered weighted IFSPG aggregation operators. The salient features of these operators are discussed in detail. Further, these operators are extended to its generalized version and called generalized IFSPA or geometric aggregation operators. Then, we utilized these operators to develop an approach to solve the decision‐making problem under IF soft set environment and demonstrated with an illustrative example. A comparative analysis of existing approaches has been done for showing the validity of the proposed work.

Combined heat and power economic dispatch using integrated civilized swarm optimization and Powells pattern search method

Abstract: PSEUDO code of proposed technique.Display Omitted An optimization technique that embeds CSO and Powells search (PS) method is proposed.The proposed technique is applied to solve combined heat and power dispatch problem.CSO is having attributes of PSO and society civilization algorithm.Initially, search is performed by CSO and then PS is applied to improve the solution.The test systems having valve point loading effect and POZs constraint. An integrated technique that embeds civilized swarm optimization (CSO) and Powells pattern search (PPS) method is proposed to search economic dispatch of combined heat and power (CHP) dispatch problem. In the proposed technique, CSO is selected as global search technique and PPS is undertaken as a local search technique. Civilized swarm optimization is having attributes of particle swarm optimization (PSO) and society civilization algorithm (SCA). In CSO, mutually interacting societies forms the civilization. The positions of society particles are updated through the guidance of own leader along with their best positions. The best performing particle of CSO is further improved by PPS method based on a certain set criterion. The PPS method is based on the conjugate search direction method and does not require the gradient or Hessian matrix of the function to be optimized. The CHP dispatch problem has a mutual dependency of demand and heat-power capacity of generating units, so it requires an effective constraint handling strategy. In this work, variable reduction strategy with exterior penalty method is applied to satisfy equality constraints. The proposed technique is tested on five CHP test systems considering valve-point loading effect, prohibited operating zones constraint, and transmission losses. The obtained results are compared to the results reported in the literature and found satisfactory. Further, for verification of statistical performance of the proposed technique, t-test and Wilcoxon signed rank test is also performed.

Evaluation of the Performance of Search and Rescue Robots Using T-spherical Fuzzy Hamacher Aggregation Operators

Abstract: Multi-attribute decision-making approach is a widely used algorithm that needs some aggregation tools and several such aggregation operators have been developed in past decades to serve the purpose. Hamacher aggregation operator is one such operator which is based on Hamacher t-norm and t-conorm. It is observed that the Hamacher aggregation operators of intuitionistic fuzzy set, Pythagorean fuzzy set and that of picture fuzzy set has some limitations in their applicability. To serve the purpose, in this paper, some Hamacher aggregation operators based on T-spherical fuzzy numbers are introduced. The concepts of T-spherical fuzzy Hamacher-weighted averaging and T-spherical fuzzy Hamacher-weighted geometric aggregation operators are proposed which described four aspects of human opinion including yes, no, abstinence and refusal with no limitations. Such type of aggregation operators efficiently describes the cases that left unsolved by the existing aggregation operators. The validity of the proposed aggregation operators is examined, and some basic properties are discussed. The proposed new Hamacher aggregation operators are used to analyze the performance of search and rescue robots using a multi-attribute decision-making approach as their performance in an emergency is eminent. The proposed Hamacher aggregation operators have two variable parameters, namely q and $$\gamma $$ which affects the decision-making process and their sensitivity towards decision-making results is analyzed. A comparative analysis of the results obtained using proposed Hamacher aggregation operators in view of the variable parameters q and $$\gamma $$ is established to discuss any advantages or disadvantages.