Portfolio Management using Beetle Swarm Optimization with Penalty Method

Solanki, Rahul; Shah, Niti; Shah, Janice; Chaudhari, Sheetal

doi:10.1109/icict50816.2021.9358619

Cited by 2 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During the initial stage, the initial location of the targets is determined by the OBSO algorithm. Based on the swarm intelligent nature of beetles, the BSO algorithm is developed [22]. Here, every individual beetle defines a possible solution to the optimization problem, and every one represents a fitness value computed through the fitness function.…”

Section: Determining Target's Initial Location Using Obso Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

A Novel 3D Indoor Node Localization Technique Using Weighted Least Square Estimation with Oppositional Beetle Swarm Optimization Algorithm

Durgaprasadarao¹,

Siddaiah²

2022

IJIE

View full text Add to dashboard Cite

In this research work an effective indoor localization mechanism has been implemented for smart devices, advancements of mobile-Internet and multimedia applications. Indoor localization is one of recent technology, it is a location-based service (LBS), this work has been facilitated to commercial and civilian industries. The LSB can useful in many tools such as public security, disaster management, and positioning navigation. Several research works have been concentrated on design of accurate 2D indoor localization techniques. Since 3D indoor localization techniques offer numerous benefits compared to 2D model. In this investigation a Novel 3D Indoor Node Localization Technique has been proposed using Oppositional Beetle Swarm Optimization with Weighted Least Square Estimation (OBSO-WLSE) algorithm. The proposed OBSO- WLSE algorithm aims to develop the localization accuracy with reduced computational time. The OBSO algorithm is employed for approximating initial locations of the targets, these results can minimize NLOS error. The precise location of target has been identified through WLSE technique as well as OBSO can predict initial location. To improve the efficiency of the OBSO technique, the concept of oppositional based learning (OBL) is integrated into the traditional BSO algorithm. The designed model prototype simulation has been run on MATLAB software with NS3 Tool Box. The measures like accuracy 98.45%, sensitivity 96.34%, recall 94.67%, 3D indoor localization detection rate 19.25% improvement and throughput 97.34% have been attained. The localization error, range error and transmission range performance measures are used for experimental evolution. The results recommended that proposed model is robust for navigation associated apps.

show abstract

Section: Determining Target's Initial Location Using Obso Algorithmmentioning

confidence: 99%

“…Fig. 2 illustrates the process of Beetle's optimization model [22,23]. The proposed Beetle's optimization technique can provide target estimation which is show Mathematically, in below explanation.…”

Section: Determining Target's Initial Location Using Obso Algorithmmentioning

confidence: 99%

A Novel 3D Indoor Node Localization Technique Using Weighted Least Square Estimation with Oppositional Beetle Swarm Optimization Algorithm

Durgaprasadarao¹,

Siddaiah²

2022

IJIE

View full text Add to dashboard Cite

show abstract

Elaboration of an Algorithm for Solving Hierarchical Inverse Problems in Applied Economics

Gribanova

2022

Mathematics

View full text Add to dashboard Cite

One of the key tools in an organization’s performance management is the goal tree, which is used for solving both direct and inverse problems. This research deals with goal setting based on a model of the future by presenting the goal and subgoal in the form of concrete quantitative and qualitative characteristics and stepwise formation of factors. A stepwise solution to a factor generation problem is considered on the basis of mathematical symmetry. This paper displays an algorithm for solving hierarchical inverse problems with constraints, which is based on recursively traversing the vertices that constitute the separate characteristics. Iterative methods, modified for the case of nonlinear models and the calculation of constraints, were used to generate solutions to the subproblems. To realize the algorithm, the object-oriented architecture, which simplifies the creation and modification of software, was elaborated. Computational experiments with five types of models were conducted, and the solution to a problem related to fast-food restaurant profit generation was reviewed. The metrics of remoteness from set values and t-statistics were calculated for the purpose of testing the received results, and solutions to the subproblems, with the help of a mathematical package using optimization models and a method of inverse calculations, were also provided. The results of computational experiments speak to the compliance of the received results with set constraints and the solution of separate subproblems with the usage of the mathematical package. The cases with the highest solution accuracy reached are specified.

show abstract

Portfolio Management using Beetle Swarm Optimization with Penalty Method

Cited by 2 publications

References 10 publications

A Novel 3D Indoor Node Localization Technique Using Weighted Least Square Estimation with Oppositional Beetle Swarm Optimization Algorithm

A Novel 3D Indoor Node Localization Technique Using Weighted Least Square Estimation with Oppositional Beetle Swarm Optimization Algorithm

Elaboration of an Algorithm for Solving Hierarchical Inverse Problems in Applied Economics

Contact Info

Product

Resources

About