PSOBER: PSO based entity resolution

2021 ◽  
Vol 8 (4) ◽  
pp. 573-583
Author(s):  
Y. Aassem ◽  
◽  
I. Hafidi ◽  
H. Khalfi ◽  
N. Aboutabit ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Optimization Algorithm ◽  
Complete Information ◽  
Entity Resolution ◽  
Unsupervised Method ◽  
Resolution Problem ◽  
Partitioning Problem

Entity Resolution is the task of mapping the records within a database to their corresponding entities. The entity resolution problem presents a lot of challenges because of the absence of complete information in records, variant distribution of records for different entities and sometimes overlaps between records of different entities. In this paper, we have proposed an unsupervised method to solve this problem. The previously mentioned problem is set as a partitioning problem. Thereafter, an optimization algorithm-based technique is proposed to solve the entity resolution problem. The presented approach enables the partitioning of records across entities. A comparative analysis with the genetic algorithm over datasets proves the efficiency of the considered approach.

scholarly journals Comparative Analysis of Distributive Optimized Clustering Techniques in Cognitive Radio Networks

2018 ◽  
Vol 7 (3.27) ◽  
pp. 504 ◽  
Author(s):  
R Ganesh Babu ◽  
Dr V.Amudha
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Cognitive Radio ◽  
Convergence Rate ◽  
Optimization Algorithm ◽  
Computation Time ◽  
Radio Networks ◽  
Optimization Techniques ◽  
Dynamic Clustering ◽  
Clustering Techniques

In this paper we study and compare the performance of Distributed Firefly Optimized Clustering (DFOC) with Distributed Swarm Optimized Clustering (DSOC) optimization techniques used for the dynamic clustering. Proposed Distributed Firefly Optimized Clustering (DFOC) is an optimization algorithm  based on the function of attractiveness of firefly behavior. All the cognitive nodes move towards the brighter firefly with random velocity to form an organized cluster with least computation time. In the existing DSOC method each particle’s best position and velocity are evaluated according to the objective function until an optimum global best position is reached. The convergence rate of DSOC is similar to Genetic Algorithm (GA). The proposed DFOC, the SU power is reduced to 7.34% for 100 numbers of SUs.compared to DSOC.  

Comparative Analysis of Determinant Elimination Method, Ant Colony Algorithms and Genetic Algorithm

2014 ◽  
Vol 624 ◽  
pp. 509-511
Author(s):  
Xin Fu
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Optimization Algorithm ◽  
Ant Colony ◽  
Optimal Solutions ◽  
Optimal Test ◽  
Test Set ◽  
Elimination Method ◽  
Ant Colony Algorithms ◽  
Test Sets

In this paper, the analysis of optimizing test sets of which the optimal solutions are already known is made first. Then the optimization results and execution time of Determinant Elimination Method, Ant Colony Algorithms as well as Genetic Algorithm are compared. At last, Based on the concept of optimal test set proposed in this paper, plenty of test sets which need to be optimized are randomly generated. The optimization algorithm proposed in this paper is also used to optimize the test sets and the consequences of optimization is desirable.

scholarly journals Comparative Analysis of Genetic Algorithm with Swarm Intelligence Algorithms

2021 ◽  
pp. 493-497
Author(s):  
Ganga Devi D
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Comparative Analysis ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Traveling Salesman ◽  
Hard Problem ◽  
Ant Colony Optimization Algorithm ◽  
Swarm Optimization ◽  
Np Hard Problem

Traveling Salesman problem is the most recognized NP-hard problem for the researches in the field of computer science which focused on optimization. TSP finds the minimum travelling distance between given set of cities by traversing each of these cities only once except the starting city. This study discusses the salesman problem by presenting Particle Swarm Optimization Algorithm (PSO), Ant Colony Optimization algorithm (ACO) and Genetic Algorithm (GA) which intends to solve the problem. In this paper, these algorithms are applied on the benchmark TSP dataset Oliver 30. Also, the paper provides comparison between these algorithms and this comparison helps to choose the better algorithm.

scholarly journals Multi-user Remote Lab: Timetable Scheduling Using Simplex Nondominated Sorting Genetic Algorithm

2021 ◽  
Vol 2 (2) ◽  
pp. 1-13
Author(s):  
Seid Miad Zandavi ◽  
Vera Chung ◽  
Ali Anaissi
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Simplex Algorithm ◽  
Local Optimum ◽  
Hybrid Optimization Algorithm ◽  
Multimodal Function ◽  
Remote Laboratories ◽  
Remote Lab ◽  
Timetable Problem

The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. The hybrid optimization algorithm, hybridization of the Nelder-Mead Simplex algorithm, and Non-dominated Sorting Genetic Algorithm (NSGA), named Simplex Non-dominated Sorting Genetic Algorithm (SNSGA), is proposed to optimize the timetable problem for the remote laboratories to coordinate shared access. The proposed algorithm utilizes the Simplex algorithm in terms of exploration and NSGA for sorting local optimum points with consideration of potential areas. SNSGA is applied to difficult nonlinear continuous multimodal functions, and its performance is compared with hybrid Simplex Particle Swarm Optimization, Simplex Genetic Algorithm, and other heuristic algorithms. The results show that SNSGA has a competitive performance to address timetable problems.

A Comparative Analysis of Metaheuristic Approaches for Multidimensional Two-Way Number Partitioning Problem

2018 ◽  
Vol 43 (12) ◽  
pp. 7499-7520 ◽  
Author(s):  
Mehmet Hacibeyoglu ◽  
Kemal Alaykiran ◽  
Ayse Merve Acilar ◽  
Vahit Tongur ◽  
Erkan Ulker
Keyword(s):  
Comparative Analysis ◽  
Partitioning Problem ◽  
Number Partitioning

scholarly journals RELEVANCE OF INFORMATION AND CONTRACTUAL MODALITY OF AESTHETIC MEDICINE: A COMPARATIVE ANALYSIS BETWEEN SPANISH AND POLISH CASE-LAW

2019 ◽  
Vol 35 (4) ◽  
pp. 103-111
Author(s):  
Dominika Rymkiewicz
Keyword(s):  
Comparative Analysis ◽  
Crucial Role ◽  
Complete Information ◽  
Case Law ◽  
Aesthetic Medicine ◽  
Fast Pace ◽  
To Receive

Aesthetic medicine has been developing at a fast pace in recent years. It is necessary and ethical for anyone who undergoes any of these treatments to receive complete information on its implementation methods, as well as its consequences andadverse effects. Only once the person who would be affected by these procedures obtains truthful and impartial information, can he or she provide a legally binding consent to undergo a procedure. Thus, the information received by the patient plays a crucial role since it underlies the subject’s decision concerning the treatment.

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