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Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm for Solving Optimal Reactive Power Dispatch Problem Lenin, Kanagasabai
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 1 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

In this work Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm (HGPSOS) has been done for solving the power dispatch problem. Genetic particle swarm optimization problem has been hybridized with Symbiotic organisms search (SOS) algorithm to solve the problem. Genetic particle swarm optimization algorithm is formed by combining the Particle swarm optimization algorithm (PSO) with genetic algorithm (GA). Symbiotic organisms search algorithm is based on the actions between two different organisms in the ecosystem- mutualism, commensalism and parasitism. Exploration process has been instigated capriciously and every organism specifies a solution with fitness value. Projected HGPSOS algorithm improves the quality of the search. Proposed HGPSOS algorithm is tested in IEEE 30, bus test system- power loss minimization, voltage deviation minimization and voltage stability enhancement has been attained.

Clustering method for spread pattern analysis of corona-virus (COVID-19) infection in Iran Azarafza, Mehdi; Azarafza, Mohammad; AkgÃ¼n, Haluk
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 1 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

The COVID-19 is outbreak from China and infected more than 131,652 people and caused 7,300 deaths in Iran. Unfortunately, the infection numbers and deaths are still increasing rapidly which has put the world on the catastrophic abyss edge. Application of data mining to perform pattern recognition of infection is mainly used for preparing the spread mapping which considered in this work for spatiotemporal distribution assessment and spread pattern analysis of corona-virus (COVID-19) infection in Iran

Clustering method for spread pattern analysis of corona-virus (COVID-19) infection in Iran Azarafza, Mehdi; Azarafza, Mohammad; Akgün, Haluk
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 1 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

The COVID-19 is outbreak from China and infected more than 131,652 people and caused 7,300 deaths in Iran. Unfortunately, the infection numbers and deaths are still increasing rapidly which has put the world on the catastrophic abyss edge. Application of data mining to perform pattern recognition of infection is mainly used for preparing the spread mapping which considered in this work for spatiotemporal distribution assessment and spread pattern analysis of corona-virus (COVID-19) infection in Iran

Analysis of Capacity, Speed, and Degree of Saturation of Intersections and Roads Isradi, Muhammad; Dwiatmoko, Hermanto; Setiawan, Muhammad Ikhsan; Supriyatno, Dadang
Journal of Applied Science, Engineering, Technology, and Education Vol. 2 No. 2 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

No traffic-signal intersection located on Jalan Serang and Jalan Curug, Tangerang Regency often causes traffic congestion. Many side barriers activities of vehicles inhibit the movement of traffic flow. The toll-road access, which is not far from the intersection, makes the queue long enough to enter Jl. Raya Serang also affects the performance of the surroundings. The study aims to determine the performance of the above intersection this time, which is measured by the capacity, degree of saturation, speed, queuing opportunities, density, and level of services. Field surveys and further analysis of the calculations that have been carried out show the intersection performance. The peak traffic volume occurred on Wednesday, February 5 2020, at 3877 pcu / hour at 07.00 - 08.00 WIB, with a capacity (C) of 2937 pcu / hour. From the available data, the DS value is 1.32. at the Service level F.

Analysis of Capacity, Speed, and Degree of Saturation of Intersections and Roads Isradi, Muhammad; Dwiatmoko, Hermanto; Setiawan, Muhammad Ikhsan; Supriyatno, Dadang
Journal of Applied Science, Engineering, Technology, and Education Vol. 2 No. 2 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

No traffic-signal intersection located on Jalan Serang and Jalan Curug, Tangerang Regency often causes traffic congestion. Many side barriers activities of vehicles inhibit the movement of traffic flow. The toll-road access, which is not far from the intersection, makes the queue long enough to enter Jl. Raya Serang also affects the performance of the surroundings. The study aims to determine the performance of the above intersection this time, which is measured by the capacity, degree of saturation, speed, queuing opportunities, density, and level of services. Field surveys and further analysis of the calculations that have been carried out show the intersection performance. The peak traffic volume occurred on Wednesday, February 5 2020, at 3877 pcu / hour at 07.00 - 08.00 WIB, with a capacity (C) of 2937 pcu / hour. From the available data, the DS value is 1.32. at the Service level F.

Factual Power Loss Diminution by Enhanced Frog Leaping Algorithm Lenin, Kanagasabai
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 2 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

This paper proposes Enhanced Frog Leaping Algorithm (EFLA) to solve the optimal reactive power problem. Frog leaping algorithm (FLA) replicates the procedure of frogs passing though the wetland and foraging deeds. Set of virtual frogs alienated into numerous groups known as â€œmemeplexesâ€. Frogâ€™s positionâ€™s turn out to be closer in every memeplex after few optimization runs and certainly, this crisis direct to premature convergence. In the proposed Enhanced Frog Leaping Algorithm (EFLA) the most excellent frog information is used to augment the local search in each memeplex and initiate to the exploration bound acceleration. To advance the speed of convergence two acceleration factors are introduced in the exploration plan formulation. Proposed Enhanced Frog Leaping Algorithm (EFLA) has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.

Factual Power Loss Diminution by Enhanced Frog Leaping Algorithm Lenin, Kanagasabai
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 2 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

This paper proposes Enhanced Frog Leaping Algorithm (EFLA) to solve the optimal reactive power problem. Frog leaping algorithm (FLA) replicates the procedure of frogs passing though the wetland and foraging deeds. Set of virtual frogs alienated into numerous groups known as â€œmemeplexesâ€. Frogâ€™s positionâ€™s turn out to be closer in every memeplex after few optimization runs and certainly, this crisis direct to premature convergence. In the proposed Enhanced Frog Leaping Algorithm (EFLA) the most excellent frog information is used to augment the local search in each memeplex and initiate to the exploration bound acceleration. To advance the speed of convergence two acceleration factors are introduced in the exploration plan formulation. Proposed Enhanced Frog Leaping Algorithm (EFLA) has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.

Solving Optimal Reactive Power Dispatch Problem by Chaotic Based Brain Storm Optimization Algorithm Lenin, Kanagasabai
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 2 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

In this work Chaotic Predator-Prey Brain Storm Optimization (CPS) algorithm is proposed to solve optimal reactive power dispatch problem. Predatorâ€“Prey Brain Storm Optimization position cluster centers to execute as predators, accordingly it will progress towards enhanced positions, although the left over thoughts do as preys; consequently they move far from their neighboring predators. In the projected algorithm chaotic theory has been applied to enhance the quality of the exploration. Ergodicity and indiscretion are utilized in the CPS algorithm, such that projected algorithm will not get trapped in the local optimal solution. Chaotic predator-prey brain storm optimization (CPS) algorithm has been tested in standard IEEE 30 bus test system and results show the projected algorithm reduced the real power loss effectively.

Solving Optimal Reactive Power Dispatch Problem by Chaotic Based Brain Storm Optimization Algorithm Lenin, Kanagasabai
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 2 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

In this work Chaotic Predator-Prey Brain Storm Optimization (CPS) algorithm is proposed to solve optimal reactive power dispatch problem. Predatorâ€“Prey Brain Storm Optimization position cluster centers to execute as predators, accordingly it will progress towards enhanced positions, although the left over thoughts do as preys; consequently they move far from their neighboring predators. In the projected algorithm chaotic theory has been applied to enhance the quality of the exploration. Ergodicity and indiscretion are utilized in the CPS algorithm, such that projected algorithm will not get trapped in the local optimal solution. Chaotic predator-prey brain storm optimization (CPS) algorithm has been tested in standard IEEE 30 bus test system and results show the projected algorithm reduced the real power loss effectively.

Forging An Optimized Bayesian Network Model With Selected Parameters For Detection of The Coronavirus In Delta State of Nigeria Ojugo, Arnold; Otakore, Oghenevwede Debby
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 1 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

Machine learning algorithm have become veritable tools for effective decision support towards the construction of systems that assist experts (individuals) in their field of exploits and endeavor with regards to problematic tasks.. They are best suited for tasks where data is explored and exploited; and cases where the dataset contains noise, partial truth, ambiguities and in cases where there is shortage of datasets. For this study, we employ the Bayesian network to construct a model trained towards a target system that can help predict best parameters used for classification of the novel coronavirus (covid-19). Data was collected from Federal Medical Center Epidemiology laboratory (a centralized databank for all cases of the covid-19 in Delta State). Data was split into training and investigation (test) dataset for the target system. Results show high predictive capability.

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Abstract

Abstract

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Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Ansari Saleh Ahmar

Contact Email journal@ahmar.id

Phone -

Journal Mail Official journal@ahmar.id

Editorial Address http://jurnal.ahmar.id/index.php/asci/about/editorialTeam

Location Unknown, Unknown INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Ansari Saleh Ahmar

Contact Email
journal@ahmar.id

Phone
-

Journal Mail Official
journal@ahmar.id

Editorial Address
http://jurnal.ahmar.id/index.php/asci/about/editorialTeam

Location
Unknown,

Unknown

INDONESIA