Search results for: Emotional Intelligence
235 Analytics Model in a Telehealth Center Based on Cloud Computing and Local Storage
Authors: L. Ramirez, E. Guillén, J. Sánchez
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Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.Keywords: Analytics, telemedicine, internet of things, cloud computing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1554234 Protein Residue Contact Prediction using Support Vector Machine
Authors: Chan Weng Howe, Mohd Saberi Mohamad
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Protein residue contact map is a compact representation of secondary structure of protein. Due to the information hold in the contact map, attentions from researchers in related field were drawn and plenty of works have been done throughout the past decade. Artificial intelligence approaches have been widely adapted in related works such as neural networks, genetic programming, and Hidden Markov model as well as support vector machine. However, the performance of the prediction was not generalized which probably depends on the data used to train and generate the prediction model. This situation shown the importance of the features or information used in affecting the prediction performance. In this research, support vector machine was used to predict protein residue contact map on different combination of features in order to show and analyze the effectiveness of the features.Keywords: contact map, protein residue contact, support vector machine, protein structure prediction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1882233 Interpreting the Out-of-Control Signals of Multivariate Control Charts Employing Neural Networks
Authors: Francisco Aparisi, José Sanz
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Multivariate quality control charts show some advantages to monitor several variables in comparison with the simultaneous use of univariate charts, nevertheless, there are some disadvantages. The main problem is how to interpret the out-ofcontrol signal of a multivariate chart. For example, in the case of control charts designed to monitor the mean vector, the chart signals showing that it must be accepted that there is a shift in the vector, but no indication is given about the variables that have produced this shift. The MEWMA quality control chart is a very powerful scheme to detect small shifts in the mean vector. There are no previous specific works about the interpretation of the out-of-control signal of this chart. In this paper neural networks are designed to interpret the out-of-control signal of the MEWMA chart, and the percentage of correct classifications is studied for different cases.
Keywords: Multivariate quality control, Artificial Intelligence, Neural Networks, Computer Applications
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2490232 The Impact of Online Advertising on Consumer Purchase Behavior Based on Malaysian Organizations
Authors: Naser Zourikalatehsamad, Seyed Abdorreza Payambarpour, Ibrahim Alwashali, Zahra Abdolkarimi
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The paper aims to evaluate the effect of online advertising on consumer purchase behavior in Malaysian organizations. The paper has potential to extend and refine theory. A survey was distributed among Students of UTM university during the winter 2014 and 160 responses were collected. Regression analysis was used to test the hypothesized relationships of the model. Result shows that the predictors (cost saving factor, convenience factor and customized product or services) have positive impact on intention to continue seeking online advertising.Keywords: Consumer purchase, convenience, customized product, cost saving, customization, flow theory, mass communication, online advertising ads, online advertising measurement, online advertising mechanism, online intelligence system, self-confidence, willingness to purchase.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13552231 Model of Optimal Centroids Approach for Multivariate Data Classification
Authors: Pham Van Nha, Le Cam Binh
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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 895230 Three-Dimensional Off-Line Path Planning for Unmanned Aerial Vehicle Using Modified Particle Swarm Optimization
Authors: Lana Dalawr Jalal
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This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex threedimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.Keywords: Obstacle Avoidance, Particle Swarm Optimization, Three-Dimensional Path Planning Unmanned Aerial Vehicles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2031229 Affective Adaptation Design for Better Gaming Experiences
Authors: Ollie Hall, Salma ElSayed
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Affective adaptation is a creative way for game designers to add an extra layer of engagement to their productions. When player’s emotions are an explicit factor in mechanics design, endless possibilities for imaginative gameplay emerge. Whilst gaining popularity, existing affective game research mostly runs controlled experiments in restrictive settings and rely on one or more specialist devices for measuring player’s emotional state. These conditions albeit effective, are not necessarily realistic. Moreover, the simplified narrative and intrusive wearables may not be suitable for players. This exploratory study investigates delivering an immersive affective experience in the wild with minimal requirements, in an attempt for the average developer to reach the average player. A puzzle game is created with rich narrative and creative mechanics. It employs both explicit and implicit adaptation and only requires a web camera. Participants played the game on their own machines in various settings. Whilst it was rated feasible, very engaging and enjoyable, it remains questionable whether a fully immersive experience was delivered due to the limited sample size.
Keywords: affective games, dynamic adaptation, emotion recognition, game design
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 821228 Integrating LCA into PDM for Ecodesign
Authors: H. Ostad-Ahmad-Ghorabi, T. Rahmani, D. Gerhard
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Product Data Management (PDM) systems for Computer Aided Design (CAD) file management are widely established in design processes. This management system is indispensable for design collaboration or when design task distribution is present. It is thus surprising that engineering design curricula has not paid much attention in the education of PDM systems. This is also the case for eduction of ecodesign and environmental evaluation of products. With the rise of sustainability as a strategic aspect in companies, environmental concerns are becoming a key issue in design. This paper discusses the establishment of a PDM platform to be used among technical and vocational schools in Austria. The PDM system facilitates design collaboration among these schools. Further, it will be discussed how the PDM system has been prepared in order to facilitate environmental evaluation of parts, components and subassemblies of a product. By integrating a Business Intelligence solution, environmental Life Cycle Assessment and communication of results is enabled.Keywords: CAD, Engineering Design, Design Education, ProductLife Cycle, Sustainability
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1975227 Data Structures and Algorithms of Intelligent Web-Based System for Modular Design
Authors: Ivan C. Mustakerov, Daniela I. Borissova
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In recent years, new product development became more and more competitive and globalized, and the designing phase is critical for the product success. The concept of modularity can provide the necessary foundation for organizations to design products that can respond rapidly to market needs. The paper describes data structures and algorithms of intelligent Web-based system for modular design taking into account modules compatibility relationship and given design requirements. The system intelligence is realized by developed algorithms for choice of modules reflecting all system restrictions and requirements. The proposed data structure and algorithms are illustrated by case study of personal computer configuration. The applicability of the proposed approach is tested through a prototype of Web-based system.
Keywords: Data structures, algorithms, intelligent web-based system, modular design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1802226 On Pseudo-Random and Orthogonal Binary Spreading Sequences
Authors: Abhijit Mitra
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Different pseudo-random or pseudo-noise (PN) as well as orthogonal sequences that can be used as spreading codes for code division multiple access (CDMA) cellular networks or can be used for encrypting speech signals to reduce the residual intelligence are investigated. We briefly review the theoretical background for direct sequence CDMA systems and describe the main characteristics of the maximal length, Gold, Barker, and Kasami sequences. We also discuss about variable- and fixed-length orthogonal codes like Walsh- Hadamard codes. The equivalence of PN and orthogonal codes are also derived. Finally, a new PN sequence is proposed which is shown to have certain better properties than the existing codes.
Keywords: Code division multiple access, pseudo-noise codes, maximal length, Gold, Barker, Kasami, Walsh-Hadamard, autocorrelation, crosscorrelation, figure of merit.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6038225 Machine Learning Methods for Environmental Monitoring and Flood Protection
Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer
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More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4076224 A Rough Sets Approach for Relevant Internet/Web Online Searching
Authors: Erika Martinez Ramirez, Rene V. Mayorga
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The internet is constantly expanding. Identifying web links of interest from web browsers requires users to visit each of the links listed, individually until a satisfactory link is found, therefore those users need to evaluate a considerable amount of links before finding their link of interest; this can be tedious and even unproductive. By incorporating web assistance, web users could be benefited from reduced time searching on relevant websites. In this paper, a rough set approach is presented, which facilitates classification of unlimited available e-vocabulary, to assist web users in reducing search times looking for relevant web sites. This approach includes two methods for identifying relevance data on web links based on the priority and percentage of relevance. As a result of these methods, a list of web sites is generated in priority sequence with an emphasis of the search criteria.Keywords: Web search, Web Mining, Rough Sets, Web Intelligence, Intelligent Portals, Relevance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1544223 Management Decision System for the Documentary Archives in the Library of a Public Moroccan Institution: Case of Sultan Moulay Slimane University, Beni Mellal
Authors: Jaouad Oukrich, Belaid Bouikhalene, Noureddine Askour
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This paper deals with the problem of management of information resources in libraries of the public institution Sultan Moulay Slimane University (SMSU) in order to analyze the satisfaction of the readers, and allow university leaders to make better strategic and instant decisions. For this, the integration of an integrated management decision library system is a priority program of higher education, as part of the Digital Morocco, which has a proactive policy to develop the use of new technologies information and communication in higher institutions. This operational information system can provide better services to the students and for the leaders. Our approach is to integrate the tools of business intelligence (BI) in the library management by using power BI.Keywords: PMB, integrated library management system, ILMS, document, SMSU, power BI, satisfaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1892222 Using Swarm Intelligence for Improving Accuracy of Fuzzy Classifiers
Authors: Hassan M. Elragal
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This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle swarm optimization (PSO). Two different fuzzy classifiers are considered and optimized. The first classifier is based on Mamdani fuzzy inference system (M_PSO fuzzy classifier). The second classifier is based on Takagi- Sugeno fuzzy inference system (TS_PSO fuzzy classifier). The parameters of the proposed fuzzy classifiers including premise (antecedent) parameters, consequent parameters and structure of fuzzy rules are optimized using PSO. Experimental results show that higher classification accuracy can be obtained with a lower number of fuzzy rules by using the proposed PSO fuzzy classifiers. The performances of M_PSO and TS_PSO fuzzy classifiers are compared to other fuzzy based classifiersKeywords: Fuzzy classifier, Optimization of fuzzy systemparameters, Particle swarm optimization, Pattern classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2331221 Introducing an Image Processing Base Idea for Outdoor Children Caring
Authors: Hooman Jafarabadi
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In this paper application of artificial intelligence for baby and children caring is studied. Then a new idea for injury prevention and safety announcement is presented by using digital image processing. The paper presents the structure of the proposed system. The system determines the possibility of the dangers for children and babies in yards, gardens and swimming pools or etc. In the presented idea, multi camera System is used and receiver videos are processed to find the hazardous areas then the entrance of children and babies in the determined hazardous areas are analyzed. In this condition the system does the programmed action capture, produce alarm or tone or send message.Keywords: Baby and children Care and Nursing, Intelligent Control Systems for Nursing, Electronic Care and Nursing, Dangers and safety for children and babies, Motion detection, Expert danger alarm systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1862220 Fuzzy-Genetic Optimal Control for Four Degreeof Freedom Robotic Arm Movement
Authors: V. K. Banga, R. Kumar, Y. Singh
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In this paper, we present optimal control for movement and trajectory planning for four degrees-of-freedom robot using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs) for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like; Movement, Friction and Settling Time in robotic arm movement have been compensated using Fuzzy logic and Genetic Algorithms. The development of a fuzzy genetic optimization algorithm is presented and discussed. The result are compared only GA and Fuzzy GA. This paper describes genetic algorithms, which is designed to optimize robot movement and trajectory. Though the model represents is a general model for redundant structures and could represent any n-link structures. The result is a complete trajectory planning with Fuzzy logic and Genetic algorithms demonstrating the flexibility of this technique of artificial intelligence.Keywords: Inverse kinematics, Genetic algorithms (GAs), Fuzzy logic (FL), Trajectory planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2280219 Methodology for Developing an Intelligent Tutoring System Based on Marzano’s Taxonomy
Authors: Joaquin Navarro Perales, Ana Lidia Franzoni Velázquez, Francisco Cervantes Pérez
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The Mexican educational system faces diverse challenges related with the quality and coverage of education. The development of Intelligent Tutoring Systems (ITS) may help to solve some of them by helping teachers to customize their classes according to the performance of the students in online courses. In this work, we propose the adaptation of a functional ITS based on Bloom’s taxonomy called Sistema de Apoyo Generalizado para la Enseñanza Individualizada (SAGE), to measure student’s metacognition and their emotional response based on Marzano’s taxonomy. The students and the system will share the control over the advance in the course, so they can improve their metacognitive skills. The system will not allow students to get access to subjects not mastered yet. The interaction between the system and the student will be implemented through Natural Language Processing techniques, thus avoiding the use of sensors to evaluate student’s response. The teacher will evaluate student’s knowledge utilization, which is equivalent to the last cognitive level in Marzano’s taxonomy.
Keywords: Intelligent tutoring systems, student modelling, metacognition, affective computing, natural language processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 995218 The Comparison of Anchor and Star Schema from a Query Performance Perspective
Authors: Radek Němec
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Today's business environment requires that companies have access to highly relevant information in a matter of seconds. Modern Business Intelligence tools rely on data structured mostly in traditional dimensional database schemas, typically represented by star schemas. Dimensional modeling is already recognized as a leading industry standard in the field of data warehousing although several drawbacks and pitfalls were reported. This paper focuses on the analysis of another data warehouse modeling technique - the anchor modeling, and its characteristics in context with the standardized dimensional modeling technique from a query performance perspective. The results of the analysis show information about performance of queries executed on database schemas structured according to principles of each database modeling technique.Keywords: Data warehousing, anchor modeling, star schema, anchor schema, query performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3306217 Individuals’ Inner Wellbeing during the COVID-19 Pandemic: A Quantitative Comparison of Social Connections and Close Relationships between the UK and India
Authors: Maria Spanoudaki, Pauldy C. J. Otermans, Dev Aditya
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Relationships form an integral part of our everyday wellbeing. In this study, the focus is on Inner Wellbeing which can be described as an individuals' thoughts and feelings about what they can do and be. Relationships can come in many forms and can be divided into Social Connections (thoughts and feelings about the social network people can establish and rely on), and Close Relationships (thoughts and feeling about the emotional support people can receive from significant others or their close, intimate circle). The purpose of this study is to compare the Social Connections and Close Relationship dimensions of Inner Wellbeing during the COVID-19 pandemic between the UK and India. As part of the study, 392 participants in the UK and 205 participants India completed an online questionnaire using the Inner Wellbeing scale. Factor analyses showed that the construct of Inner Wellbeing can be described as one factor for the UK sample whereas it can be described as two factors (one focusing on positive items and one focusing on negative items) for the Indian sample. Results showed that during COVID-19, Social Connections were significantly different in the UK compared to India, whereas there is no significant difference for Close Relationships. The implications on relationships and wellbeing are discussed in detail.
Keywords: Social networks, relationship maintenance, relationship satisfaction, inner wellbeing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 807216 The Application of Adaptive Tabu Search Algorithm and Averaging Model to the Optimal Controller Design of Buck Converters
Authors: T. Sopapirm, K-N. Areerak, K-L. Areerak, A. Srikaew
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The paper presents the applications of artificial intelligence technique called adaptive tabu search to design the controller of a buck converter. The averaging model derived from the DQ and generalized state-space averaging methods is applied to simulate the system during a searching process. The simulations using such averaging model require the faster computational time compared with that of the full topology model from the software packages. The reported model is suitable for the work in the paper in which the repeating calculation is needed for searching the best solution. The results will show that the proposed design technique can provide the better output waveforms compared with those designed from the classical method.Keywords: Buck converter, adaptive tabu search, DQ method, generalized state-space averaging method, modeling and simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1828215 Learning Styles of University Students in Bangkok: The Characteristics and the Relevant Instructional Context
Authors: Chaiwat Tantarangsee
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The purposes of this study are 1) to identify learning styles of university students in Bangkok, and 2) to study the frequency of the relevant instructional context of the identified learning styles. Learning Styles employed in this study are those of Honey and Mumford, which include 1) Reflectors, 2) Theorists, 3) Pragmatists, and 4) Activists. The population comprises 1383 students and 5 lecturers. Research tools are 2 questionnaires – one used for identifying students- learning styles, and the other used for identifying the frequency of the relevant instructional context of the identified learning styles. The research findings reveal that 32.30 percent - are Activists, while 28.10 percent are Theorists, 20.10 are Reflectors, and 19.50 are Pragmatists. In terms of the relevant instructional context of the identified 4 learning styles, it is found that the frequency level of the instructional context is totally in high level. Moreover, 2 lists of the context being conducted most frequently are 'Lead'in activity to review background knowledge,- and 'Information retrieval report.' And these two activities serve the learning styles of theorists and activists. It is, therefore, suggested that more instructional context supporting the activists, the majority of the population, learning best by doing, as well as emotional learning situation should be added.Keywords: Instructional Context, Learning Styles, Learning Style Preference, and Learning Style Questionnaire.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1845214 Coupled Dynamics in Host-Guest Complex Systems Duplicates Emergent Behavior in the Brain
Authors: Sergio Pissanetzky
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The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.
Keywords: AI, artificial intelligence, complex system, object oriented, OO, refactoring.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2080213 Mining Implicit Knowledge to Predict Political Risk by Providing Novel Framework with Using Bayesian Network
Authors: Siavash Asadi Ghajarloo
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Nowadays predicting political risk level of country has become a critical issue for investors who intend to achieve accurate information concerning stability of the business environments. Since, most of the times investors are layman and nonprofessional IT personnel; this paper aims to propose a framework named GECR in order to help nonexpert persons to discover political risk stability across time based on the political news and events. To achieve this goal, the Bayesian Networks approach was utilized for 186 political news of Pakistan as sample dataset. Bayesian Networks as an artificial intelligence approach has been employed in presented framework, since this is a powerful technique that can be applied to model uncertain domains. The results showed that our framework along with Bayesian Networks as decision support tool, predicted the political risk level with a high degree of accuracy.Keywords: Bayesian Networks, Data mining, GECRframework, Predicting political risk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2166212 Arabic Word Semantic Similarity
Authors: Faaza A, Almarsoomi, James D, O'Shea, Zuhair A, Bandar, Keeley A, Crockett
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This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done for English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. In this paper, an Arabic benchmark dataset of 70 word pairs is presented. New methods and best possible available techniques have been used in this study to produce the Arabic dataset. This includes selecting and creating materials, collecting human ratings from a representative sample of participants, and calculating the overall ratings. This dataset will make a substantial contribution to future work in the field of Arabic WSS and hopefully it will be considered as a reference basis from which to evaluate and compare different methodologies in the field.
Keywords: Arabic categories, benchmark dataset, semantic similarity, word pair, stimulus Arabic words
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3087211 Particle Swarm Optimization Based PID Power System Stabilizer for a Synchronous Machine
Authors: Gowrishankar Kasilingam
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This paper proposes a swarm intelligence method that yields optimal Proportional-Integral-Derivative (PID) Controller parameters of a power system stabilizer (PSS) in a single machine infinite bus system. The proposed method utilizes the Particle Swarm Optimization (PSO) algorithm approach to generate the optimal tuning parameters. The paper is modeled in the MATLAB Simulink Environment to analyze the performance of a synchronous machine under several load conditions. At the same operating point, the PID-PSS parameters are also tuned by Ziegler-Nichols method. The dynamic performance of proposed controller is compared with the conventional Ziegler-Nichols method of PID tuning controller to demonstrate its advantage. The analysis reveals the effectiveness of the proposed PSO based PID controller.
Keywords: Particle Swarm Optimization, PID Controller, Power System Stabilizer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3023210 A Multiagent System for Distributed Systems Management
Authors: H. M. Kelash, H. M. Faheem, M. Amoon
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The demand for autonomous resource management for distributed systems has increased in recent years. Distributed systems require an efficient and powerful communication mechanism between applications running on different hosts and networks. The use of mobile agent technology to distribute and delegate management tasks promises to overcome the scalability and flexibility limitations of the currently used centralized management approach. This work proposes a multiagent system that adopts mobile agents as a technology for tasks distribution, results collection, and management of resources in large-scale distributed systems. A new mobile agent-based approach for collecting results from distributed system elements is presented. The technique of artificial intelligence based on intelligent agents giving the system a proactive behavior. The presented results are based on a design example of an application operating in a mobile environment.Keywords: distributed management, distributed systems, efficiency, mobile agent, multiagent, response time
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2075209 New Approach for Load Modeling
Authors: S. Chokri
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Load modeling is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.
Keywords: Neural network, Load Forecasting, Fuzzy inference, Machine learning, Fuzzy modeling and rule extraction, Support Vector Regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2191208 A Survey of Response Generation of Dialogue Systems
Authors: Yifan Fan, Xudong Luo, Pingping Lin
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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.Keywords: Retrieval, generative, deep learning, response generation, knowledge.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1187207 Tehran-Tabriz Intelligent Highway
Authors: P. Parvizi, F. Norouzifard, S.Mohammadi
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The need to implement intelligent highways is much more emphasized with the growth of vehicle production line as well as vehicle intelligence. The control of intelligent vehicles in order to reduce human error and boost ease congestion is not accomplished solely by the aid of human resources. The present article is an attempt to introduce an intelligent control system based on a single central computer. In this project, central computer, without utilizing Global Positioning System (GPS), is capable of tracking all vehicles, crisis management and control, traffic guidance and recording traffic crimes along the highway. By the help of RFID technology, vehicles are connected to computerized systems, intelligent light poles and other available hardware along the way. By the aid of Wimax communicative technology, all components of the system are virtually connected together through local and global networks devised in them and the energy of the network is provided by the solar cells installed on the intelligent light poles.Keywords: intelligent highway, intelligent light pole, highway automation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1746206 Intelligent Swarm-Finding in Formation Control of Multi-Robots to Track a Moving Target
Authors: Anh Duc Dang, Joachim Horn
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This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbors are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.
Keywords: Formation control, potential field method, obstacle avoidance, swarm intelligence, multi-agent systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2177