Renewable Energy sources are the center of attraction for research and development all over the world nowadays, the demand of a lasting cheap source of energy that is environmental friendly, is the main challenge recently. Energy Harvesting is a new technology that is going to make a revolution in the coming decade. Energy Harvesting is a technique to provide alternative sources of energy that are environmental friendly and low in cost. Radio Frequency Energy Harvesting is one of the methods to provide electrical energy from the ambient Radio Frequency waves that already exists in the environment. Radio Frequency Energy Harvesting can provide a world with battery less devices. With Radio Frequency (RF) Energy Harvesting, the true mobility can be achieved where mobile devices do not depend on centralized power sources for charging, instead they make use of the existing energy in the environment. This paper presents a simulation survey on different frequencies and the effect of these frequencies on the output power efficiency. The simulation results provide an optimum novel relationship between the frequency used and the size of the circuit for a radio frequency energy harvesting model with optimum output efficiency.
{"title":"Frequency Survey Simulation for Developing Novel Radio Frequency Energy Harvesting Model","authors":"H. Elanzeery, R. Guindi","doi":"10.1109/UKSim.2012.71","DOIUrl":"https://doi.org/10.1109/UKSim.2012.71","url":null,"abstract":"Renewable Energy sources are the center of attraction for research and development all over the world nowadays, the demand of a lasting cheap source of energy that is environmental friendly, is the main challenge recently. Energy Harvesting is a new technology that is going to make a revolution in the coming decade. Energy Harvesting is a technique to provide alternative sources of energy that are environmental friendly and low in cost. Radio Frequency Energy Harvesting is one of the methods to provide electrical energy from the ambient Radio Frequency waves that already exists in the environment. Radio Frequency Energy Harvesting can provide a world with battery less devices. With Radio Frequency (RF) Energy Harvesting, the true mobility can be achieved where mobile devices do not depend on centralized power sources for charging, instead they make use of the existing energy in the environment. This paper presents a simulation survey on different frequencies and the effect of these frequencies on the output power efficiency. The simulation results provide an optimum novel relationship between the frequency used and the size of the circuit for a radio frequency energy harvesting model with optimum output efficiency.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115577947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Sandaruwan, N. Kodikara, C. Keppitiyagama, R. Rosa, M. Jayawardena, P. Samarasinghe
Perception enhanced real-time Virtual Reality (VR) applications are used in various fields such as education and entertainment. The physical and behavioral realism of such applications are important in different perspectives. We have developed a perception enhanced real-time VR solution for maritime applications such as naval training, water way designs and simulate military scenes. In this paper, we present brief description of a six degrees of freedom (6-DOF) real-time mathematical ship motion simulation model and validation techniques for physical/ behavioral realism of a perception enhanced maritime VR environment. The user perceived physical and behavioral realism of the VR solution is investigated with user tests and preliminary results are presented.
{"title":"User Perception of the Physical & Behavioral Realism of a Maritime Virtual Reality Environment","authors":"D. Sandaruwan, N. Kodikara, C. Keppitiyagama, R. Rosa, M. Jayawardena, P. Samarasinghe","doi":"10.1109/UKSim.2012.32","DOIUrl":"https://doi.org/10.1109/UKSim.2012.32","url":null,"abstract":"Perception enhanced real-time Virtual Reality (VR) applications are used in various fields such as education and entertainment. The physical and behavioral realism of such applications are important in different perspectives. We have developed a perception enhanced real-time VR solution for maritime applications such as naval training, water way designs and simulate military scenes. In this paper, we present brief description of a six degrees of freedom (6-DOF) real-time mathematical ship motion simulation model and validation techniques for physical/ behavioral realism of a perception enhanced maritime VR environment. The user perceived physical and behavioral realism of the VR solution is investigated with user tests and preliminary results are presented.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123214568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this research we use a learning method called SAQ-Learning to use for agents in a single-issue bargaining process. SAQ-Learning algorithm is an improved version of Q-Learning algorithm that benefits from the Metropolis criterion of Simulated Annealing (SA) algorithm to overcome the challenge of finding a balance between exploration and exploitation. Q-Learning is one the most important types of Reinforcement Learning (RL) because of the fact that it does not need the transition model of the environment. Artificial Intelligence (AI) approaches have attracted interest in solving bargaining problem. This is because Game Theory (GT) needs some unrealistic assumptions to solve bargaining problem. Presence of perfectly rational agents is an example of these assumptions. Therefore by designing SAQ-Learning agents to bargain with each other over price, we gained higher performance in case of settlement rate, average payoff, and the time an agent needs to find his optimal policy. This learning method can be a suitable learning algorithm for automated online bargaining agents in e-commerce.
{"title":"Applying SAQ-Learning Algorithm for Trading Agents in Bilateral Bargaining","authors":"S. Jamali, K. Faez","doi":"10.1109/UKSim.2012.39","DOIUrl":"https://doi.org/10.1109/UKSim.2012.39","url":null,"abstract":"In this research we use a learning method called SAQ-Learning to use for agents in a single-issue bargaining process. SAQ-Learning algorithm is an improved version of Q-Learning algorithm that benefits from the Metropolis criterion of Simulated Annealing (SA) algorithm to overcome the challenge of finding a balance between exploration and exploitation. Q-Learning is one the most important types of Reinforcement Learning (RL) because of the fact that it does not need the transition model of the environment. Artificial Intelligence (AI) approaches have attracted interest in solving bargaining problem. This is because Game Theory (GT) needs some unrealistic assumptions to solve bargaining problem. Presence of perfectly rational agents is an example of these assumptions. Therefore by designing SAQ-Learning agents to bargain with each other over price, we gained higher performance in case of settlement rate, average payoff, and the time an agent needs to find his optimal policy. This learning method can be a suitable learning algorithm for automated online bargaining agents in e-commerce.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123961577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
India has highest incidence of heart related diseases in the world. If no initiative is taken to check the disease the most predictable and preventable among all chronic diseases, India will have 62 million heart patients by 2015. Myocardial ischemia (also known as angina) is a heart condition caused by a temporary lack of oxygen-rich blood to the heart. Cardiac ischemia (CI) is a heart disease that covers heart issues caused by narrowing of the arteries which makes less oxygenated blood to reach the heart muscle. This may lead to heart attack with no prior warning. This paper introduces the work that has been done to distinguish the Electrocardiogram (ECG) of a normal healthy human from that of an ischemia patient. Fast Fourier Transform (FFT) on ECG Signal was used to extract information and providing the basis with which a signal suggesting predisposition of the patient who suffers from Cardiac ischemia. The main aim is to design algorithm that enable the doctors to diagnose cardiac ischemia on the basis of spectral analysis of an ECG signal. 4 min. of ECG of any patient is enough to detect possibility of ischemia. Normal Sinus Rhythm Data is obtained from MIT-BIH NSR Database. Ischemia data is obtained from European ST-T Database. The data is taken for duration of 1 hour. The algorithm was tested on MIT-BIH database and European ST-T Database and the verification of results using MATLAB is done. This concept can be utilized to analyze ECG signals to identify other heart diseases.
{"title":"Identification of Cardiac Ischemia Using Spectral Domain Analysis of Electrocardiogram","authors":"R. Valupadasu, B. R. Chunduri","doi":"10.1109/UKSim.2012.22","DOIUrl":"https://doi.org/10.1109/UKSim.2012.22","url":null,"abstract":"India has highest incidence of heart related diseases in the world. If no initiative is taken to check the disease the most predictable and preventable among all chronic diseases, India will have 62 million heart patients by 2015. Myocardial ischemia (also known as angina) is a heart condition caused by a temporary lack of oxygen-rich blood to the heart. Cardiac ischemia (CI) is a heart disease that covers heart issues caused by narrowing of the arteries which makes less oxygenated blood to reach the heart muscle. This may lead to heart attack with no prior warning. This paper introduces the work that has been done to distinguish the Electrocardiogram (ECG) of a normal healthy human from that of an ischemia patient. Fast Fourier Transform (FFT) on ECG Signal was used to extract information and providing the basis with which a signal suggesting predisposition of the patient who suffers from Cardiac ischemia. The main aim is to design algorithm that enable the doctors to diagnose cardiac ischemia on the basis of spectral analysis of an ECG signal. 4 min. of ECG of any patient is enough to detect possibility of ischemia. Normal Sinus Rhythm Data is obtained from MIT-BIH NSR Database. Ischemia data is obtained from European ST-T Database. The data is taken for duration of 1 hour. The algorithm was tested on MIT-BIH database and European ST-T Database and the verification of results using MATLAB is done. This concept can be utilized to analyze ECG signals to identify other heart diseases.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124150076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Soleimani, A. Ahmadi, Mohammad Bavandpour, A. Amirsoleimani, Mark Zwolinski
Since biological neural systems contain big number of neurons working in parallel, simulation of such dynamic system is a real challenge. The main objective of this paper is to speed up the simulation performance of SystemC designs at the RTL abstraction level using the high degree of parallelism afforded by graphics processors (GPUs) for large scale SNN with proposed structure in pattern classification field. Simulation results show 100 times speedup for the proposed SNN structure on the GPU compared with the CPU version. In addition, CPU memory has problems when trained for more than 120K cells but GPU can simulate up to 40 million neurons.
{"title":"A Large Scale Digital Simulation of Spiking Neural Networks (SNN) on Fast SystemC Simulator","authors":"H. Soleimani, A. Ahmadi, Mohammad Bavandpour, A. Amirsoleimani, Mark Zwolinski","doi":"10.1109/UKSIM.2012.105","DOIUrl":"https://doi.org/10.1109/UKSIM.2012.105","url":null,"abstract":"Since biological neural systems contain big number of neurons working in parallel, simulation of such dynamic system is a real challenge. The main objective of this paper is to speed up the simulation performance of SystemC designs at the RTL abstraction level using the high degree of parallelism afforded by graphics processors (GPUs) for large scale SNN with proposed structure in pattern classification field. Simulation results show 100 times speedup for the proposed SNN structure on the GPU compared with the CPU version. In addition, CPU memory has problems when trained for more than 120K cells but GPU can simulate up to 40 million neurons.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125105212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Krishna Doddapaneni, E. Ever, O. Gemikonakli, I. Malavolta, L. Mostarda, H. Muccini
Energy consumption of nodes is a crucial factor that constrains the networks life time for Wireless Sensor Networks (WSNs). WSNs are composed of small sensors equipped with low-power devices, and have limited battery power supply. The main concern in existing architectural and optimisation studies is to prolong the network lifetime. The lifetime of the sensor nodes is affected by different components such as the microprocessor, the sensing module and the wireless transmitter/receiver. The existing works mainly consider these components to decide on best deployment, topology, protocols and so on. Recent studies have also considered the monitoring and evaluation of the path loss caused by environmental factors. Path loss is always considered in isolation from the higher layers such as application and network. It is necessary to combine path loss computations used in physical layer, with information from upper layers such as application layer for a more realistic evaluation. In this paper, a simulation-based study is presented that uses path-loss model and application layer information in order to predict the network lifetime. Physical environment is considered as well. We show that when path-loss is introduced, increasing the transmission power is needed to reduce the amount of packets lost. This presents a tradeoff between the residual energy and the successful transmission rate when more realistic settings are employed for simulation. It is a challenging task to optimise the transmission power of WSNs, in presence of path loss, because although increasing the transmission power reduces the residual energy, it also reduces the number of retransmissions required.
{"title":"Path Loss Effect on Energy Consumption in a WSN","authors":"Krishna Doddapaneni, E. Ever, O. Gemikonakli, I. Malavolta, L. Mostarda, H. Muccini","doi":"10.1109/UKSim.2012.87","DOIUrl":"https://doi.org/10.1109/UKSim.2012.87","url":null,"abstract":"Energy consumption of nodes is a crucial factor that constrains the networks life time for Wireless Sensor Networks (WSNs). WSNs are composed of small sensors equipped with low-power devices, and have limited battery power supply. The main concern in existing architectural and optimisation studies is to prolong the network lifetime. The lifetime of the sensor nodes is affected by different components such as the microprocessor, the sensing module and the wireless transmitter/receiver. The existing works mainly consider these components to decide on best deployment, topology, protocols and so on. Recent studies have also considered the monitoring and evaluation of the path loss caused by environmental factors. Path loss is always considered in isolation from the higher layers such as application and network. It is necessary to combine path loss computations used in physical layer, with information from upper layers such as application layer for a more realistic evaluation. In this paper, a simulation-based study is presented that uses path-loss model and application layer information in order to predict the network lifetime. Physical environment is considered as well. We show that when path-loss is introduced, increasing the transmission power is needed to reduce the amount of packets lost. This presents a tradeoff between the residual energy and the successful transmission rate when more realistic settings are employed for simulation. It is a challenging task to optimise the transmission power of WSNs, in presence of path loss, because although increasing the transmission power reduces the residual energy, it also reduces the number of retransmissions required.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128570246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The problem of optimizing a linear objective function, given a number of linear constraints has been a long standing problem ever since the times of Kantorovich, Dantzig and John von Neumann. These developments have been followed by a different approach pioneered by Khachiyan and Karmarkar. In this paper we attempt a new approach for solving an old optimization problem in a novel manner, in the sense that we devise a method that reduces the dimension of the problem step by step and interestingly is recursive. The method can be extended to other types of optimization problems in convex space, e.g. for solving a linear optimization problem subject to nonlinear constraints in a convex region.
{"title":"A Novel Algorithm for Linear Programming","authors":"K. Eswaran","doi":"10.1109/UKSim.2012.54","DOIUrl":"https://doi.org/10.1109/UKSim.2012.54","url":null,"abstract":"The problem of optimizing a linear objective function, given a number of linear constraints has been a long standing problem ever since the times of Kantorovich, Dantzig and John von Neumann. These developments have been followed by a different approach pioneered by Khachiyan and Karmarkar. In this paper we attempt a new approach for solving an old optimization problem in a novel manner, in the sense that we devise a method that reduces the dimension of the problem step by step and interestingly is recursive. The method can be extended to other types of optimization problems in convex space, e.g. for solving a linear optimization problem subject to nonlinear constraints in a convex region.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128691963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artificial Neural Network algorithms has been tested for the classification of patterns and best among them was implemented for the application of brain tumour classification as specified by World Health Organization standards via 2D MR images. The technique of Rajasekaran and Pai (sBAM) was found to give most successful results of classifying tumour into their correct classes. The computation time taken by sBAM was also less as compared with other algorithms. sBAM technique wasn't tested on brain tumour MR images before but when it is subjected to test, it provided prominent results. The success rate of sBAM was also relatively high with its counterparts.
{"title":"Comparison of Different Artificial Neural Networks for Brain Tumour Classification via Magnetic Resonance Images","authors":"Yawar Rehman, C. F. Azim","doi":"10.1109/UKSim.2012.13","DOIUrl":"https://doi.org/10.1109/UKSim.2012.13","url":null,"abstract":"Artificial Neural Network algorithms has been tested for the classification of patterns and best among them was implemented for the application of brain tumour classification as specified by World Health Organization standards via 2D MR images. The technique of Rajasekaran and Pai (sBAM) was found to give most successful results of classifying tumour into their correct classes. The computation time taken by sBAM was also less as compared with other algorithms. sBAM technique wasn't tested on brain tumour MR images before but when it is subjected to test, it provided prominent results. The success rate of sBAM was also relatively high with its counterparts.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131660198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhandos Yessenbayev, Muslima Karabalayeva, A. Sharipbayev
The traditional classification of Kazakh vowels, the most complicated objects in Kazakh phonetics, is somewhat inadequate in that it does not uniquely identify each vowel. Moreover, the formant structure of the vowels has not been investigated yet, which would potentially be useful in many applications regarding speech processing. In this work a formant analysis of Kazakh vowels is performed. This analysis suggests a new natural classification system which precisely describes each vowel. The proposed classification is supported by the membership function introduced and by the geometric interpretation derived from the constructed vowel space. Further, from this mathematical model some linguistic statements are inferred, which are related to the real phonological processes.
{"title":"Formant Analysis and Mathematical Model of Kazakh Vowels","authors":"Zhandos Yessenbayev, Muslima Karabalayeva, A. Sharipbayev","doi":"10.1109/UKSim.2012.66","DOIUrl":"https://doi.org/10.1109/UKSim.2012.66","url":null,"abstract":"The traditional classification of Kazakh vowels, the most complicated objects in Kazakh phonetics, is somewhat inadequate in that it does not uniquely identify each vowel. Moreover, the formant structure of the vowels has not been investigated yet, which would potentially be useful in many applications regarding speech processing. In this work a formant analysis of Kazakh vowels is performed. This analysis suggests a new natural classification system which precisely describes each vowel. The proposed classification is supported by the membership function introduced and by the geometric interpretation derived from the constructed vowel space. Further, from this mathematical model some linguistic statements are inferred, which are related to the real phonological processes.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131715099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Generally, conventional controllers are characterized by too longs settling and rise times. In order to solve this problem, suitable fuzzy logic controllers have been designed. However, some intelligent techniques can be added during the controllers designing phase. In the literature, the employed methods are Genetic Algorithms and Neural Networks. The first ones are good search methods whereas the others ones have the capability to learn from data. In this paper, an optimized genetic-neuro-fuzzy controller is proposed. This controller works in according with a real-time optimization algorithm which optimally combines the features of Fuzzy Logic, Genetic Algorithms and Neural Networks. The genetic procedures search the optimal membership functions whereas the neural methods optimize the fuzzy rules. The target is to reduce the settling time and rise time with overshoot equal to zero. The novelty of this approach is that the optimization procedures occur at the same time and not separately. The results show that the settling time and the rise time are reduced by comparing them with the same quantities of optimized PD and PID controllers. Moreover, the designed controller improves the timing performance of conventional and intelligent controllers.
{"title":"Improving Settling and Rise Times of Controllers via Intelligent Algorithms","authors":"D. Pelusi","doi":"10.1109/UKSim.2012.34","DOIUrl":"https://doi.org/10.1109/UKSim.2012.34","url":null,"abstract":"Generally, conventional controllers are characterized by too longs settling and rise times. In order to solve this problem, suitable fuzzy logic controllers have been designed. However, some intelligent techniques can be added during the controllers designing phase. In the literature, the employed methods are Genetic Algorithms and Neural Networks. The first ones are good search methods whereas the others ones have the capability to learn from data. In this paper, an optimized genetic-neuro-fuzzy controller is proposed. This controller works in according with a real-time optimization algorithm which optimally combines the features of Fuzzy Logic, Genetic Algorithms and Neural Networks. The genetic procedures search the optimal membership functions whereas the neural methods optimize the fuzzy rules. The target is to reduce the settling time and rise time with overshoot equal to zero. The novelty of this approach is that the optimization procedures occur at the same time and not separately. The results show that the settling time and the rise time are reduced by comparing them with the same quantities of optimized PD and PID controllers. Moreover, the designed controller improves the timing performance of conventional and intelligent controllers.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131803802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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