Rescheduling Based Congestion Management Method Using Hybrid Grey Wolf Optimization - Grasshopper Optimization Algorithm in Power System

Roy, Rupam Gupta

doi:10.46253/jcmps.v2i1.a2

Cited by 39 publications

(8 citation statements)

References 9 publications

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“…Though the conventional SSO 34 model hasa selection of enhancements; it undergoes specifiedlimits like local convergence etc. To prevail over the disadvantages of traditional SSO, the conception of SSA 35 is combined with it to introduce a new algorithm termed SS‐SSOAD 36–39 …”

Section: Proposed Ss‐ssoad Algorithm For Optimal Mpa Designmentioning

confidence: 99%

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Hybrid optimization algorithm for optimal designing of microstrip patch antenna

Guttula

Ramesh

Mannepally

2023

Concurrency and Computation

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Microstrip Patch Antennas (MPAs) are generally renowned for their adaptability regarding feasible geometries, which makes them appropriate for numerous diverse conditions. The suitability to integrate and the trivial structure with microwave incorporated circuits was said to be the major advantage among several advantages. MPA poses constricted bandwidth; thus it has a complication while tuning. In addition, MPAs are renowned for their reduced gain. As a result, there is a necessity to raise the gain and bandwidth of MPA. This work intends to put forward a novel approach that gets a non-linear objective for assisting the modeling of solution spaces for antenna constraints. Thus, "Salp Swarm based Shark Smell Optimization (SS-SSO) that hybrids the concepts of Salp Swarm Algorithm (SSA) and Shark Smell Optimization (SSO)" is developed that tuned the constraints of MPA. The implication of the developed approach is to boost the antenna gain by optimal electing of dielectric value, patch length, substrate width, and thickness of MPA.

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Section: Proposed Ss‐ssoad Algorithm For Optimal Mpa Designmentioning

confidence: 99%

“…To prevail over the disadvantages of traditional SSO, the conception of SSA 35 is combined with it to introduce a new algorithm termed SS-SSOAD. [36][37][38][39] SS-SSOAD includes four fundamental phases namely, "initialization, forward movement, rotational movement, and position update. "…”

Section: Proposed Ss-ssoad Modelmentioning

confidence: 99%

Hybrid optimization algorithm for optimal designing of microstrip patch antenna

Guttula

Ramesh

Mannepally

2023

Concurrency and Computation

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“…These noise levels were indicated as noise levels 1, 2, and 3 for immune cells, tumour cells, and normal cells. Here, adopted technique has experimented with the traditional techniques namely GWO [14], GA [15], GSA [16], and PSO [15].…”

Section: Experimentation Proceduresmentioning

confidence: 99%

Shark Optimization Algorithm: Drug Dosage Estimation in Cancer Chemotherapy

Anbhazhagan¹

2022

JCMPS

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Chemotherapy is a medicine that is frequently exploited to treat cancer; the cancer cells widen as well as propagate more rapidly than the other cells in body. Although chemotherapy is a capable technique to analyze several types of cancers, treatment involves threat as it reasons side effects because of inappropriate drug practice. Thus, this research proposes a robust controller to control the dosage of the drug which is performed in parameter estimation. Additionally, a Modified Regularized Error Function (MREF)-Extended Kalman Filter (EKF) is adopted to approximate tumor cells as well as it can be used for different circumstances. In addition, the overfitting problem happens at the time of the drug dosage estimation which is resolved by exploiting this method. Furthermore, to improve the proposed model performance, the primary condition of EKF is fine-tuned using Shark Optimization Algorithm (SOA). Finally, the preeminence of the developed technique is revealed regarding the error analysis.

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“…With this intension, this paper introduces the concept of hybridization of LA and CSO, in such a way that the proposed CSM-LA algorithm can accomplish the aforementioned challenges and offers excellent results. In fact, the hybrid optimizations are reported to be capable for solving search issues (Marsaline Beno et al , 2014; Thomas and Rangachar, 2018; GuptaRoy, 2019). Traditionally, in LA, the territorial lion and lioness denoted by Amale and Afemale carries out crossover and mutation to create a maximum of 8 cubs and forms a cub pool.…”

Section: Optimal Subcarrier Power and Price Allocation Via Proposed C...mentioning

confidence: 99%

Macrocell–femtocell resource allocation via hybrid optimization algorithm

Mohite¹,

Kolekar²

2021

IJIUS

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PurposeFemtocells are low-power, inexpensive base stations (BS) used in business enterprises or homes. They could offer higher SNR in a smaller coverage area to enhance the data rates and QoS. Deployment of femtocell is expected to the witness constant development in upcoming years. Despite of all these benefits, there are certain challenges to be resolved that includes management of overlaying MC, interference among femtocells and the resource allocation between 2 tiers.Design/methodology/approachThis work analyses the issues on cross-tier interfering and resource allocation alleviation in “full-duplex (FD) Orthogonal Frequency Division Multiple Access (OFDMA) oriented Heterogeneous Networks (HetNets) that includes macrocell as well as underlying femtocells”. This work concerns on three foremost contributions: portraying a single objective issue including subcarrier allocation, price allocation and power allocation of macrocell–femtocell networks. Moreover, this work introduces a novel Cat Swarm Mated-Lion algorithm (CSM-LA) for solving the defined optimization problem in macrocell–femtocell networks. At last, the supremacy of adopted scheme is proved over traditional models regarding statistical and convergence analysis.FindingsBy concerning the cost function, the developed CSM-LA attained 87.5, 60, 93.75 and 93.75% better than LM, WOA, LA and CSO respectively. For utility analysis, it accomplished 70.58% better than LM, 88.23% superior to GWO, 85.88% superior to WOA and 88.23% better than CSO. For statistical analysis, the median performance of developed CSM-LA attained better results, which was 80.52% superior to LA, 80.74% better than GWO, 72% superior to WOA and 48.7% better than LA. Hence, the developed CSM-LA proved its performance in terms of improved results and revealed its betterment over the conventional models.Originality/valueThis paper adopts a latest optimization algorithm called CSM-LA for analyzing the issues on cross-tier interfering and resource allocation alleviation in full-duplex (FD) orthogonal frequency division multiple access (OFDMA) oriented heterogeneous networks (HetNets). This is the first work that utilizes CSM-LA framework that proposes a new CSM-LA model for power control and resource allocation by considering the multi-objectives like price, subcarrier and power as well.

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Rescheduling Based Congestion Management Method Using Hybrid Grey Wolf Optimization - Grasshopper Optimization Algorithm in Power System

Cited by 39 publications

References 9 publications

Hybrid optimization algorithm for optimal designing of microstrip patch antenna

Hybrid optimization algorithm for optimal designing of microstrip patch antenna

Shark Optimization Algorithm: Drug Dosage Estimation in Cancer Chemotherapy

Macrocell–femtocell resource allocation via hybrid optimization algorithm

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