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Electrical and Computer Engineering

Electrical and Computer Engineering Faculty Research & Creative Works

2004

Particle Swarm Optimization

Articles 1 - 6 of 6

Full-Text Articles in Engineering

Unmanned Vehicle Navigation Using Swarm Intelligence, Sheetal Doctor, Ganesh K. Venayagamoorthy Jan 2004

Unmanned Vehicle Navigation Using Swarm Intelligence, Sheetal Doctor, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

Unmanned vehicles are used to explore physical areas where humans are unable to go due to different constraints. There have been various algorithms that have been used to perform this task. This paper explores swarm intelligence for searching a given problem space for a particular target(s). The work in this paper has two parts. In the first part, a set of randomized unmanned vehicles are deployed to locate a single target. In the second part, the randomized unmanned vehicles are deployed to locate various targets and are then converged at one of targets of a particular interest. Each of the …


Swarm Intelligence For Digital Circuits Implementation On Field Programmable Gate Arrays Platforms, Ganesh K. Venayagamoorthy, Venu Gopal Gudise Jan 2004

Swarm Intelligence For Digital Circuits Implementation On Field Programmable Gate Arrays Platforms, Ganesh K. Venayagamoorthy, Venu Gopal Gudise

Electrical and Computer Engineering Faculty Research & Creative Works

Field programmable gate arrays (FPGAs) are becoming increasingly important implementation platforms for digital circuits. One of the necessary requirements to effectively utilize the FPGA's resources is an efficient placement and routing mechanism. This paper presents an optimization technique based on swarm intelligence for FPGA placement and routing. Mentor graphics technology mapping netlist file is used to generate initial FPGA placements and routings which are then optimized by particle swarm optimization (PSO). Results for the implementation of a binary coded decimal bidirectional counter and an arithmetic logic unit on a Xilinx FPGA show that PSO is a potential technique for solving …


Navigation Of Mobile Sensors Using Pso And Embedded Pso In A Fuzzy Logic Controller, Ganesh K. Venayagamoorthy, Sheetal Doctor Jan 2004

Navigation Of Mobile Sensors Using Pso And Embedded Pso In A Fuzzy Logic Controller, Ganesh K. Venayagamoorthy, Sheetal Doctor

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents novel structures for optimization and communication of a swarm of mobile sensors or robots for maximizing local and global tasks such as firefighting, landmine detection, radioactivity detection, etc. The navigation of the sensors is carried out using two strategies. The first strategy is based on particle swarm optimization (PSO) and the second strategy is based on a swarm of fuzzy logic based controllers. In addition, the membership functions and the rules of the fuzzy logic controller (FLC) are optimized using the PSO algorithm. Navigation of mobile sensors is considered in this paper to locate desirable target sources …


Time Series Prediction With Recurrent Neural Networks Using A Hybrid Pso-Ea Algorithm, Nian Zhang, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Xindi Cai Jan 2004

Time Series Prediction With Recurrent Neural Networks Using A Hybrid Pso-Ea Algorithm, Nian Zhang, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Xindi Cai

Electrical and Computer Engineering Faculty Research & Creative Works

To predict the 100 missing values from the time series consisting of 5000 data given for the IJCNN 2004 time series prediction competition, we applied an architecture which automates the design of recurrent neural networks using a new evolutionary learning algorithm. This new evolutionary learning algorithm is based on a hybrid of particle swarm optimization (PSO) and evolutionary algorithm (EA). By combining the searching abilities of these two global optimization methods, the evolution of individuals is no longer restricted to be in the same generation, and better performed individuals may produce offspring to replace those with poor performance. The novel …


Optimal Pso For Collective Robotic Search Applications, Ganesh K. Venayagamoorthy, Venu Gopal Gudise, Sheetal Doctor Jan 2004

Optimal Pso For Collective Robotic Search Applications, Ganesh K. Venayagamoorthy, Venu Gopal Gudise, Sheetal Doctor

Electrical and Computer Engineering Faculty Research & Creative Works

Unmanned vehicles/mobile robots are of particular interest in target tracing applications since there are many areas where a human cannot explore. Different means of control have been investigated for unmanned vehicles with various algorithms like genetic algorithms, evolutionary computations, neural networks etc. This work presents the application of particle swarm optimization (PSO) for collective robotic search. The performance of the PSO algorithm depends on various parameters called quality factors and these parameters are determined using a secondary PSO. Results are presented to show that the performance of PSO algorithm and search is improved for a single and multiple target searches.


Fpga Placement And Routing Using Particle Swarm Optimization, Ganesh K. Venayagamoorthy, Venu Gopal Gudise Jan 2004

Fpga Placement And Routing Using Particle Swarm Optimization, Ganesh K. Venayagamoorthy, Venu Gopal Gudise

Electrical and Computer Engineering Faculty Research & Creative Works

Field programmable gate arrays (FPGAs) are becoming increasingly important implementation platforms for digital circuits. One of the necessary requirements to effectively utilize the FPGA's fixed resources is an efficient placement and routing mechanism. This paper presents particle swarm optimization (PSO) for FPGA placement and routing. Preliminary results for the implementation of an arithmetic logic unit on a Xilinx FPGA show that PSO is a potential technique for solving the placement and routing problem.