Search results for: Ordinal Optimization
1593 Robotic Arm Control with Neural Networks Using Genetic Algorithm Optimization Approach
Authors: A. Pajaziti, H. Cana
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In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.
Keywords: Robotic Arm, Neural Network, Genetic Algorithm, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35871592 CSTR Control by Using Model Reference Adaptive Control and PSO
Authors: Neha Khanduja
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This paper presents a comparative analysis of continuously stirred tank reactor (CSTR) control based on adaptive control and optimal tuning of PID control based on particle swarm optimization. In the design of adaptive control, Model reference adaptive control (MRAC) scheme is used, in which the adaptation law have been developed by MIT rule & Lyapunov’s rule. In PSO control parameters of PID controller is tuned by using the concept of particle swarm optimization to get optimized operating point for minimum integral square error (ISE) condition. The results show the adjustment of PID parameters converting into the optimal operating point and the good control response can be obtained by the PSO technique.Keywords: Model reference adaptive control (MRAC), optimal control, particle swarm optimization (PSO).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23251591 Comparison between Post- and Oxy-Combustion Systems in a Petroleum Refinery Unit Using Modeling and Optimization
Authors: Farooq A. Al-Sheikh, Ali Elkamel, William A. Anderson
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A fluidized catalytic cracking unit (FCCU) is one of the effective units in many refineries. Modeling and optimization of FCCU were done by many researchers in past decades, but in this research, comparison between post- and oxy-combustion was studied in the regenerator-FCCU. Therefore, a simplified mathematical model was derived by doing mass/heat balances around both reactor and regenerator. A state space analysis was employed to show effects of the flow rates variables such as air, feed, spent catalyst, regenerated catalyst and flue gas on the output variables. The main aim of studying dynamic responses is to figure out the most influencing variables that affect both reactor/regenerator temperatures; also, finding the upper/lower limits of the influencing variables to ensure that temperatures of the reactors and regenerator work within normal operating conditions. Therefore, those values will be used as side constraints in the optimization technique to find appropriate operating regimes. The objective functions were modeled to be maximizing the energy in the reactor while minimizing the energy consumption in the regenerator. In conclusion, an oxy-combustion process can be used instead of a post-combustion one.
Keywords: FCCU modeling, optimization, oxy-combustion post-combustion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9091590 Optimization of Shear Frame Structures Applying Various Forms of Wavelet Transforms
Authors: Seyed Sadegh Naseralavi, Sohrab Nemati, Ehsan Khojastehfar, Sadegh Balaghi
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In the present research, various formulations of wavelet transform are applied on acceleration time history of earthquake. The mentioned transforms decompose the strong ground motion into low and high frequency parts. Since the high frequency portion of strong ground motion has a minor effect on dynamic response of structures, the structure is excited by low frequency part. Consequently, the seismic response of structure is predicted consuming one half of computational time, comparing with conventional time history analysis. Towards reducing the computational effort needed in seismic optimization of structure, seismic optimization of a shear frame structure is conducted by applying various forms of mentioned transformation through genetic algorithm.
Keywords: Time history analysis, wavelet transform, optimization, earthquake.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7851589 A Fuzzy Mixed Integer Multi-Scenario Portfolio Optimization Model
Authors: M. S. Osman, A. A. Tharwat, I. A. El-Khodary, A. G. Chalabi
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In this paper, we propose a multiple objective optimization model with respect to portfolio selection problem for investors looking forward to diversify their equity investments in a number of equity markets. Based on Markowitz-s M-V model we developed a Fuzzy Mixed Integer Multi-Objective Nonlinear Programming Problem (FMIMONLP) to maximize the investors- future gains on equity markets, reach the optimal proportion of the budget to be invested in different equities. A numerical example with a comprehensive analysis on artificial data from several equity markets is presented in order to illustrate the proposed model and its solution method. The model performed well compared with the deterministic version of the model.
Keywords: Equity Markets, Future Scenarios, PortfolioSelection, Multiple Criteria Fuzzy Optimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19641588 Application of Particle Swarm Optimization for Economic Load Dispatch and Loss Reduction
Authors: N. Phanthuna, J. Jaturacherdchaiskul, S. Lerdvanittip, S. Auchariyamet
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This paper proposes a particle swarm optimization (PSO) technique to solve the economic load dispatch (ELD) problems. For the ELD problem in this work, the objective function is to minimize the total fuel cost of all generator units for a given daily load pattern while the main constraints are power balance and generation output of each units. Case study in the test system of 40-generation units with 6 load patterns is presented to demonstrate the performance of PSO in solving the ELD problem. It can be seen that the optimal solution given by PSO provides the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction.
Keywords: Particle Swarm Optimization, Economic Load Dispatch, Loss Reduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18881587 Artificial Neural Network based Parameter Estimation and Design Optimization of Loop Antenna
Authors: Kumaresh Sarmah, Kandarpa Kumar Sarma
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Artificial Neural Network (ANN)s are best suited for prediction and optimization problems. Trained ANNs have found wide spread acceptance in several antenna design systems. Four parameters namely antenna radiation resistance, loss resistance, efficiency, and inductance can be used to design an antenna layout though there are several other parameters available. An ANN can be trained to provide the best and worst case precisions of an antenna design problem defined by these four parameters. This work describes the use of an ANN to generate the four mentioned parameters for a loop antenna for the specified frequency range. It also provides insights to the prediction of best and worst-case design problems observed in applications and thereby formulate a model for physical layout design of a loop antenna.Keywords: MLP, ANN, parameter, prediction, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15461586 Multi-Case Multi-Objective Simulated Annealing (MC-MOSA): New Approach to Adapt Simulated Annealing to Multi-objective Optimization
Authors: Abdelfatteh Haidine, Ralf Lehnert
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In this paper a new approach is proposed for the adaptation of the simulated annealing search in the field of the Multi-Objective Optimization (MOO). This new approach is called Multi-Case Multi-Objective Simulated Annealing (MC-MOSA). It uses some basics of a well-known recent Multi-Objective Simulated Annealing proposed by Ulungu et al., which is referred in the literature as U-MOSA. However, some drawbacks of this algorithm have been found, and are substituted by other ones, especially in the acceptance decision criterion. The MC-MOSA has shown better performance than the U-MOSA in the numerical experiments. This performance is further improved by some other subvariants of the MC-MOSA, such as Fast-annealing MC-MOSA, Re-annealing MCMOSA and the Two-Stage annealing MC-MOSA.Keywords: Simulated annealing, multi-objective optimization, acceptance decision criteria, re-annealing, two-stage annealing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17471585 Integrated Simulation and Optimization for Carbon Capture and Storage System
Authors: Taekyoon Park, Seok Goo Lee, Sung Ho Kim, Ung Lee, Jong Min Lee, Chonghun Han
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CO2 capture and storage/sequestration (CCS) is a key technology for addressing the global warming issue. This paper proposes an integrated model for the whole chain of CCS, from a power plant to a reservoir. The integrated model is further utilized to determine optimal operating conditions and study responses to various changes in input variables.
Keywords: CCS, Caron Dioxide, Carbon Capture and Storage, Simulation, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26701584 Study of the Effect of Inclusion of TiO2 in Active Flux on Submerged Arc Welding of Low Carbon Mild Steel Plate and Parametric Optimization of the Process by Using DEA Based Bat Algorithm
Authors: Sheetal Kumar Parwar, J. Deb Barma, A. Majumder
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Submerged arc welding is a very complex process. It is a very efficient and high performance welding process. In this present study an attempt have been done to reduce the welding distortion by increased amount of oxide flux through TiO2 in submerged arc welding process. Care has been taken to avoid the excessiveness of the adding agent for attainment of significant results. Data Envelopment Analysis (DEA) based BAT algorithm is used for the parametric optimization purpose in which DEA is used to convert multi response parameters into a single response parameter. The present study also helps to know the effectiveness of the addition of TiO2 in active flux during submerged arc welding process.Keywords: BAT algorithm, design of experiment, optimization, submerged arc welding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20021583 Locating Critical Failure Surface in Rock Slope Stability with Hybrid Model Based on Artificial Immune System and Cellular Learning Automata (CLA-AIS)
Authors: Ramin Javadzadeh, Emad Javadzadeh
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Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.
Keywords: CLA-AIS, failure surface, optimization methods, rock slope.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19991582 Improvement of Central Composite Design in Modeling and Optimization of Simulation Experiments
Authors: A. Nuchitprasittichai, N. Lerdritsirikoon, T. Khamsing
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Simulation modeling can be used to solve real world problems. It provides an understanding of a complex system. To develop a simplified model of process simulation, a suitable experimental design is required to be able to capture surface characteristics. This paper presents the experimental design and algorithm used to model the process simulation for optimization problem. The CO2 liquefaction based on external refrigeration with two refrigeration circuits was used as a simulation case study. Latin Hypercube Sampling (LHS) was purposed to combine with existing Central Composite Design (CCD) samples to improve the performance of CCD in generating the second order model of the system. The second order model was then used as the objective function of the optimization problem. The results showed that adding LHS samples to CCD samples can help capture surface curvature characteristics. Suitable number of LHS sample points should be considered in order to get an accurate nonlinear model with minimum number of simulation experiments.Keywords: Central composite design, CO2 liquefaction, Latin Hypercube Sampling, simulation – based optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7291581 A Simulation Modeling Approach for Optimization of Storage Space Allocation in Container Terminal
Authors: Gamal Abd El-Nasser A. Said, El-Sayed M. El-Horbaty
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Container handling problems at container terminals are NP-hard problems. This paper presents an approach using discrete-event simulation modeling to optimize solution for storage space allocation problem, taking into account all various interrelated container terminal handling activities. The proposed approach is applied on a real case study data of container terminal at Alexandria port. The computational results show the effectiveness of the proposed model for optimization of storage space allocation in container terminal where 54% reduction in containers handling time in port is achieved.
Keywords: Container terminal, discrete-event simulation, optimization, storage space allocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29301580 Hexagonal Honeycomb Sandwich Plate Optimization Using Gravitational Search Algorithm
Authors: A. Boudjemai, A. Zafrane, R. Hocine
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Honeycomb sandwich panels are increasingly used in the construction of space vehicles because of their outstanding strength, stiffness and light weight properties. However, the use of honeycomb sandwich plates comes with difficulties in the design process as a result of the large number of design variables involved, including composite material design, shape and geometry. Hence, this work deals with the presentation of an optimal design of hexagonal honeycomb sandwich structures subjected to space environment. The optimization process is performed using a set of algorithms including the gravitational search algorithm (GSA). Numerical results are obtained and presented for a set of algorithms. The results obtained by the GSA algorithm are much better compared to other algorithms used in this study.
Keywords: Optimization, Gravitational search algorithm, Genetic algorithm, Honeycomb plate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32821579 An Improved Particle Swarm Optimization Technique for Combined Economic and Environmental Power Dispatch Including Valve Point Loading Effects
Authors: Badr M. Alshammari, T. Guesmi
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In recent years, the combined economic and emission power dispatch is one of the main problems of electrical power system. It aims to schedule the power generation of generators in order to minimize cost production and emission of harmful gases caused by fossil-fueled thermal units such as CO, CO2, NOx, and SO2. To solve this complicated multi-objective problem, an improved version of the particle swarm optimization technique that includes non-dominated sorting concept has been proposed. Valve point loading effects and system losses have been considered. The three-unit and ten-unit benchmark systems have been used to show the effectiveness of the suggested optimization technique for solving this kind of nonconvex problem. The simulation results have been compared with those obtained using genetic algorithm based method. Comparison results show that the proposed approach can provide a higher quality solution with better performance.
Keywords: Power dispatch, valve point loading effects, multiobjective optimization, Pareto solutions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7591578 Multi-Criteria Optimization of High-Temperature Reversed Starter-Generator
Authors: Flur R. Ismagilov, Irek Kh. Khayrullin, Vyacheslav E. Vavilov, Ruslan D. Karimov, Anton S. Gorbunov, Danis R. Farrakhov
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The paper presents another structural scheme of high-temperature starter-generator with external rotor to be installed on High Pressure Shaft (HPS) of aircraft engines (AE) to implement More Electrical Engine concept. The basic materials to make this starter-generator (SG) were selected and justified. Multi-criteria optimization of the developed structural scheme was performed using a genetic algorithm and Pareto method. The optimum (in Pareto terms) active length and thickness of permanent magnets of SG were selected as a result of the optimization. Using the dimensions obtained, allowed to reduce the weight of the designed SG by 10 kg relative to a base option at constant thermal loads. Multidisciplinary computer simulation was performed on the basis of the optimum geometric dimensions, which proved performance efficiency of the design. We further plan to make a full-scale sample of SG of HPS and publish the results of its experimental research.Keywords: High-temperature starter-generator, More electrical engine, multi-criteria optimization, permanent magnet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11961577 Optimization of Agricultural Water Demand Using a Hybrid Model of Dynamic Programming and Neural Networks: A Case Study of Algeria
Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi
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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.Keywords: ater management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7121576 Ramp Rate and Constriction Factor Based Dual Objective Economic Load Dispatch Using Particle Swarm Optimization
Authors: Himanshu Shekhar Maharana, S. K .Dash
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Economic Load Dispatch (ELD) proves to be a vital optimization process in electric power system for allocating generation amongst various units to compute the cost of generation, the cost of emission involving global warming gases like sulphur dioxide, nitrous oxide and carbon monoxide etc. In this dissertation, we emphasize ramp rate constriction factor based particle swarm optimization (RRCPSO) for analyzing various performance objectives, namely cost of generation, cost of emission, and a dual objective function involving both these objectives through the experimental simulated results. A 6-unit 30 bus IEEE test case system has been utilized for simulating the results involving improved weight factor advanced ramp rate limit constraints for optimizing total cost of generation and emission. This method increases the tendency of particles to venture into the solution space to ameliorate their convergence rates. Earlier works through dispersed PSO (DPSO) and constriction factor based PSO (CPSO) give rise to comparatively higher computational time and less good optimal solution at par with current dissertation. This paper deals with ramp rate and constriction factor based well defined ramp rate PSO to compute various objectives namely cost, emission and total objective etc. and compares the result with DPSO and weight improved PSO (WIPSO) techniques illustrating lesser computational time and better optimal solution.
Keywords: Economic load dispatch, constriction factor based particle swarm optimization, dispersed particle swarm optimization, weight improved particle swarm optimization, ramp rate and constriction factor based particle swarm optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12461575 Optimization of Petroleum Refinery Configuration Design with Logic Propositions
Authors: Cheng Seong Khor, Xiao Qi Yeoh
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This work concerns the topological optimization problem for determining the optimal petroleum refinery configuration. We are interested in further investigating and hopefully advancing the existing optimization approaches and strategies employing logic propositions to conceptual process synthesis problems. In particular, we seek to contribute to this increasingly exciting area of chemical process modeling by addressing the following potentially important issues: (a) how the formulation of design specifications in a mixed-logical-and-integer optimization model can be employed in a synthesis problem to enrich the problem representation by incorporating past design experience, engineering knowledge, and heuristics; and (b) how structural specifications on the interconnectivity relationships by space (states) and by function (tasks) in a superstructure should be properly formulated within a mixed-integer linear programming (MILP) model. The proposed modeling technique is illustrated on a case study involving the alternative processing routes of naphtha, in which significant improvement in the solution quality is obtained.Keywords: Mixed-integer linear programming (MILP), petroleum refinery, process synthesis, superstructure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17151574 3-D Visualization and Optimization for SISO Linear Systems Using Parametrization of Two-Stage Compensator Design
Authors: Kazuyoshi Mori, Keisuke Hashimoto
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In this paper, we consider the two-stage compensator designs of SISO plants. As an investigation of the characteristics of the two-stage compensator designs, which is not well investigated yet, of SISO plants, we implement three dimensional visualization systems of output signals and optimization system for SISO plants by the parametrization of stabilizing controllers based on the two-stage compensator design. The system runs on Mathematica by using “Three Dimensional Surface Plots,” so that the visualization can be interactively manipulated by users. In this paper, we use the discrete-time LTI system model. Even so, our approach is the factorization approach, so that the result can be applied to many linear models.Keywords: Linear systems, visualization, optimization, two-Stage compensator design, Mathematica.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11871573 Optimization by Ant Colony Hybryde for the Bin-Packing Problem
Authors: Ben Mohamed Ahemed Mohamed, Yassine Adnan
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The problem of bin-packing in two dimensions (2BP) consists in placing a given set of rectangular items in a minimum number of rectangular and identical containers, called bins. This article treats the case of objects with a free orientation of 90Ôùª. We propose an approach of resolution combining optimization by colony of ants (ACO) and the heuristic method IMA to resolve this NP-Hard problem.
Keywords: Ant colony algorithm, bin-packing problem, heuristics methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18221572 Design of a Robust Controller for AGC with Combined Intelligence Techniques
Authors: R. N. Patel, S. K. Sinha, R. Prasad
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In this work Artificial Intelligence (AI) techniques like Fuzzy logic, Genetic Algorithms and Particle Swarm Optimization have been used to improve the performance of the Automatic Generation Control (AGC) system. Instead of applying Genetic Algorithms and Particle swarm optimization independently for optimizing the parameters of the conventional AGC with PI controller, an intelligent tuned Fuzzy logic controller (acting as the secondary controller in the AGC system) has been designed. The controller gives an improved dynamic performance for both hydrothermal and thermal-thermal power systems under a variety of operating conditions.
Keywords: Artificial intelligence, Automatic generation control, Fuzzy control, Genetic Algorithm, Particle swarm optimization, Power systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17761571 Empirical Evaluation of Performance Optimization Techniques Used in Mobile Applications
Authors: Nathar Shah, Bu Kiat Seng
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Mobile application development is different from regular application development due to the hardware resource limitations existed in the mobile platforms. In the mobile environment, the application needs to be optimized by the developer to produce optimal software with least overhead. This study discussed about performance optimization techniques that are employed in general application development, and how such techniques are performing on mobile platforms through some empirical evaluations on a mobile emulator, Nokia X3-02 and Nokia C5-03devices. The scope of the work is only confined to mobile platform based on Java Mobile edition architecture. The empirical results showed that techniques such as loop unrolling, dependency chain, and linearized getter and setter performed better by a factor of 3 to 7. Whereas declaration and initialization on the same line or separate line did not improve the performance.
Keywords: Optimization Techniques, Mobile Applications, Performance Evaluation, J2ME, Empirical Experiments
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15941570 A Biomimetic Approach for the Multi-Objective Optimization of Kinetic Façade Design
Authors: Do-Jin Jang, Sung-Ah Kim
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A kinetic façade responds to user requirements and environmental conditions. In designing a kinetic façade, kinetic patterns play a key role in determining its performance. This paper proposes a biomimetic method for the multi-objective optimization for kinetic façade design. The autonomous decentralized control system is combined with flocking algorithm. The flocking agents are autonomously reacting to sensor values and bring about kinetic patterns changing over time. A series of experiments were conducted to verify the potential and limitations of the flocking based decentralized control. As a result, it could show the highest performance balancing multiple objectives such as solar radiation and openness among the comparison group.
Keywords: Biomimicry, flocking algorithm, autonomous decentralized control, multi-objective optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13581569 A Method for Improving Dental Crown Fit-Increasing the Robustness
Authors: Kero T., Söderberg R., Andersson M., Lindkvist L.
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The introduction of mass-customization has enabled new ways to treat patients within medicine. However, the introduction of industrialized treatments has also meant new obstacles. The purpose of this study was to introduce and theoretically test a method for improving dental crown fit. The optimization method allocates support points in order to check the final variation for dental crowns. Three different types of geometries were tested and compared. The three geometries were also divided into three sub-geometries: Current method, Optimized method and Feasible method. The Optimized method, using the whole surface for support points, provided the best results. The results support the objective of the study. It also seems that the support optimization method can dramatically improve the robustness of dental crown treatments.Keywords: Bio-medicine, Dentistry, Mass-customization, Optimization and Robust design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16061568 A Hybrid Nature Inspired Algorithm for Generating Optimal Query Plan
Authors: R. Gomathi, D. Sharmila
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The emergence of the Semantic Web technology increases day by day due to the rapid growth of multiple web pages. Many standard formats are available to store the semantic web data. The most popular format is the Resource Description Framework (RDF). Querying large RDF graphs becomes a tedious procedure with a vast increase in the amount of data. The problem of query optimization becomes an issue in querying large RDF graphs. Choosing the best query plan reduces the amount of query execution time. To address this problem, nature inspired algorithms can be used as an alternative to the traditional query optimization techniques. In this research, the optimal query plan is generated by the proposed SAPSO algorithm which is a hybrid of Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithms. The proposed SAPSO algorithm has the ability to find the local optimistic result and it avoids the problem of local minimum. Experiments were performed on different datasets by changing the number of predicates and the amount of data. The proposed algorithm gives improved results compared to existing algorithms in terms of query execution time.
Keywords: Semantic web, RDF, Query optimization, Nature inspired algorithms, PSO, SA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22301567 Hybrid Artificial Bee Colony and Least Squares Method for Rule-Based Systems Learning
Authors: Ahcene Habbi, Yassine Boudouaoui
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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.
Keywords: Automatic design, learning, fuzzy rules, hybrid, swarm optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21461566 Generation Scheduling Optimization of Multi-Hydroplants: A Case Study
Authors: Shuangquan Liu, Jinwen Wang, Dada Wang
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A case study of the generation scheduling optimization of the multi-hydroplants on the Yuan River Basin in China is reported in this paper. Concerning the uncertainty of the inflows, the long/mid-term generation scheduling (LMTGS) problem is solved by a stochastic model in which the inflows are considered as stochastic variables. For the short-term generation scheduling (STGS) problem, a constraint violation priority is defined in case not all constraints are satisfied. Provided the stage-wise separable condition and low dimensions, the hydroplant-based operational region schedules (HBORS) problem is solved by dynamic programming (DP). The coordination of LMTGS and STGS is presented as well. The feasibility and the effectiveness of the models and solution methods are verified by the numerical results.Keywords: generation scheduling, multi-hydroplants, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15401565 Comparative Study on Swarm Intelligence Techniques for Biclustering of Microarray Gene Expression Data
Authors: R. Balamurugan, A. M. Natarajan, K. Premalatha
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Microarray gene expression data play a vital in biological processes, gene regulation and disease mechanism. Biclustering in gene expression data is a subset of the genes indicating consistent patterns under the subset of the conditions. Finding a biclustering is an optimization problem. In recent years, swarm intelligence techniques are popular due to the fact that many real-world problems are increasingly large, complex and dynamic. By reasons of the size and complexity of the problems, it is necessary to find an optimization technique whose efficiency is measured by finding the near optimal solution within a reasonable amount of time. In this paper, the algorithmic concepts of the Particle Swarm Optimization (PSO), Shuffled Frog Leaping (SFL) and Cuckoo Search (CS) algorithms have been analyzed for the four benchmark gene expression dataset. The experiment results show that CS outperforms PSO and SFL for 3 datasets and SFL give better performance in one dataset. Also this work determines the biological relevance of the biclusters with Gene Ontology in terms of function, process and component.
Keywords: Particle swarm optimization, Shuffled frog leaping, Cuckoo search, biclustering, gene expression data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26531564 Manipulation of Image Segmentation Using Cleverness Artificial Bee Colony Approach
Authors: Y. Harold Robinson, E. Golden Julie, P. Joyce Beryl Princess
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Image segmentation is the concept of splitting the images into several images. Image Segmentation algorithm is used to manipulate the process of image segmentation. The advantage of ABC is that it conducts every worldwide exploration and inhabitant exploration for iteration. Particle Swarm Optimization (PSO) and Evolutionary Particle Swarm Optimization (EPSO) encompass a number of search problems. Cleverness Artificial Bee Colony algorithm has been imposed to increase the performance of a neighborhood search. The simulation results clearly show that the presented ABC methods outperform the existing methods. The result shows that the algorithms can be used to implement the manipulator for grasping of colored objects. The efficiency of the presented method is improved a lot by comparing to other methods.Keywords: Color information, EPSO, ABC, image segmentation, particle swarm optimization, active contour, GMM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1282