A Hybrid Watermarking System for Securing Multi-modal Biometric Using Honey Encryption and Grasshopper Optimization Technique

A new metaheuristic swarm intelligence optimization technique, called general greenfly aphid swarm optimization algorithm, which is proposed by enhancing the performance of swarm optimization through cockroach swarm optimization algorithm. The performance of 23 benchmark functions is tested and compared with widely used algorithms, including particle swarm optimization algorithm, cockroach swarm optimization and grasshopper optimization algorithm. Numerical experiments show that the greenfly aphid swarm optimization algorithm outperforms its counterparts. Besides, to demonstrate the practical impact of the proposed algorithm, two classic engineering design problems, namely, pressure vessel design problem and himmelblau’s optimization problem, are also considered and the proposed greenfly aphid swarm optimization algorithm is shown to be competitive in those applications.

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Renewable Energy Based Economic Emission Load Dispatch Using Grasshopper Optimization Algorithm

International Journal of Swarm Intelligence Research ◽

10.4018/ijsir.2019010103 ◽

2019 ◽

Vol 10 (1) ◽

pp. 38-57 ◽

Cited By ~ 9

Author(s):

Sunanda Hazra ◽

Tapas Pal ◽

Provas Kumar Roy

Keyword(s):

Renewable Energy ◽

Wind Power ◽

Optimization Algorithm ◽

Renewable Energy Sources ◽

Optimization Technique ◽

Wind Farms ◽

Integrated Approach ◽

Fitness Value ◽

Grasshopper Optimization Algorithm ◽

Grasshopper Optimization

This article presents an integrated approach towards the economical operation of a hybrid system which consists of conventional thermal generators and renewable energy sources like windmills using a grasshopper optimization algorithm (GOA). This is based on the social interaction nature of the grasshopper, considering a carbon tax on the emissions from the thermal unit and uncertainty in wind power availability. The Weibull distribution is used for nonlinearity of wind power availability. A standard system, containing six thermal units and two wind farms, is used for testing the dispatch model of three different loads. The GOA results are compared with those obtained using a recently developed quantum-inspired particle swarm optimization (QPSO) optimization technique available in the literature. The simulation results demonstrate the efficacy and ability of GOA over the QPSO algorithm in terms of convergence rate and minimum fitness value. Performance analysis under wind power integration and emission minimization further confirms the supremacy of the GOA algorithm.

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Index-based transmission for distributed generation in voltage stability and loss control incorporating optimization technique

IAES International Journal of Artificial Intelligence (IJ-AI) ◽

10.11591/ijai.v9.i2.pp244-251 ◽

2020 ◽

Vol 9 (2) ◽

pp. 244

Author(s):

Fareed Danial Ahmad Kahar ◽

Ismail Musirin ◽

Muhamad Faliq Mohamad Nazer ◽

Shahrizal Jelani ◽

Mohd Helmi Mansor

Keyword(s):

Distributed Generation ◽

Optimization Algorithm ◽

Voltage Stability ◽

Optimization Technique ◽

Stability Index ◽

Test System ◽

Voltage Security ◽

Grasshopper Optimization Algorithm ◽

Grasshopper Optimization ◽

Loss Control

<span lang="EN-US">The integration of Distributed Generation (DG) in a distribution network may significantly affect distribution performance. With the penetration of DG, voltage security is no longer an issue in the transmission network. This paper presents a study of Distributed Generation on the IEEE 26-Bus Reliability Test System (RTS) with the use of Fast Voltage Stability Index (FVSI) for determining its location and incorporated with Grasshopper Optimization Algorithm (GOA) to optimize the sizing of the DG. The study emphasizes the power loss of the system in which a comparison between Evolutionary Programming (EP) and Grasshopper Optimization Algorithm is done to determine which optimization technique gives an optimal result for the DG solution. The results show that the proposed algorithm is able to provide a slightly better result compared to EP.</span>

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Renewable Energy Based Economic Emission Load Dispatch Using Grasshopper Optimization Algorithm

Research Anthology on Clean Energy Management and Solutions ◽

10.4018/978-1-7998-9152-9.ch036 ◽

2021 ◽

pp. 869-890

Author(s):

Sunanda Hazra ◽

Tapas Pal ◽

Provas Kumar Roy

Keyword(s):

Renewable Energy ◽

Wind Power ◽

Optimization Algorithm ◽

Carbon Tax ◽

Renewable Energy Sources ◽

Optimization Technique ◽

Wind Farms ◽

Integrated Approach ◽

Grasshopper Optimization Algorithm ◽

Grasshopper Optimization

This article presents an integrated approach towards the economical operation of a hybrid system which consists of conventional thermal generators and renewable energy sources like windmills using a grasshopper optimization algorithm (GOA). This is based on the social interaction nature of the grasshopper, considering a carbon tax on the emissions from the thermal unit and uncertainty in wind power availability. The Weibull distribution is used for nonlinearity of wind power availability. A standard system, containing six thermal units and two wind farms, is used for testing the dispatch model of three different loads. The GOA results are compared with those obtained using a recently developed quantum-inspired particle swarm optimization (QPSO) optimization technique available in the literature. The simulation results demonstrate the efficacy and ability of GOA over the QPSO algorithm in terms of convergence rate and minimum fitness value. Performance analysis under wind power integration and emission minimization further confirms the supremacy of the GOA algorithm.

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Smart Energy Management System of Environmentally Friendly Microgrid Based on Grasshopper Optimization Technique

Energies ◽

10.3390/en13195000 ◽

2020 ◽

Vol 13 (19) ◽

pp. 5000 ◽

Cited By ~ 1

Author(s):

Yehia Gad ◽

Hatem Diab ◽

Mahmoud Abdelsalam ◽

Yasser Galal

Keyword(s):

Energy Management ◽

Management System ◽

Optimization Technique ◽

Minimum Cost ◽

Energy Resources ◽

Energy Management System ◽

Renewable Energy Resources ◽

Grasshopper Optimization Algorithm ◽

Generation Cost ◽

Grasshopper Optimization

A microgrid is a group of distributed energy resources and interconnected loads that may be operated either in isolated mode or connected mode with the main utility within electrical boundaries. Microgrids may consist of different types of renewable energy resources such as photovoltaic panels, wind turbines, fuel cells, micro turbines, and storage units. It is highly recommended to manage the dependency on these resources by implementing an energy management unit to optimize the energy exchange so that the minimum cost is achieved. In this paper, an energy management system based on the grasshopper optimization algorithm (GOA) is proposed to determine the optimal power generated by the distributed generators in the microgrid which is required to minimize the total generation cost. The proposed unit is applied to a microgrid that consists of five generating units feeding residential, commercial, and industrial loads, and results are compared to other available research in literature to validate the proposed algorithm.

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Performance Improvement of OFDM Systems by Reducing Papr using SLM-Grasshopper Optimization

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.b1050.1292s319 ◽

2019 ◽

Vol 9 (2S3) ◽

pp. 204-208

Keyword(s):

Orthogonal Frequency Division Multiplexing ◽

Optimization Technique ◽

Mapping Technique ◽

Ofdm Systems ◽

Major Drawback ◽

Rate Transmission ◽

Grasshopper Optimization ◽

Selective Mapping ◽

Data Rate Transmission ◽

Peak Value

Orthogonal Frequency Division Multiplexing (OFDM) is an emerging technology which is been most commonly used for transmission of data in wireless based systems. The OFDM technique is capable of achieving more speed i.e it has higher data rate transmission which is reliable and efficient. Peak power is the major drawback while transmitting the signal which is termed as PAPR. The signals achieves high peak value while transmitting due to the presence of large subcarriers which are independent in nature. The amplitude of the signal need to be reduced. Many PAPR reductions schemes have been presented in past and the reduction is done to some extents. In this paper , a new optimisation technique i.e grasshopper optimization (GOA) is proposed. The optimization technique is combined with one of the efficient PAPR reduction technique i.e selective mapping technique. The combination of SLM-Grasshopper help in reducing the PAPR as low as possible and is also compared with other techniques like SLM-GA, SLM-FA and SLM-GWO. The experimental results are performed using matlab.

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