Search results for: random drift particle swarm optimization
2331 On Discretization of Second-order Derivatives in Smoothed Particle Hydrodynamics
Authors: R. Fatehi, M.A. Fayazbakhsh, M.T. Manzari
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Discretization of spatial derivatives is an important issue in meshfree methods especially when the derivative terms contain non-linear coefficients. In this paper, various methods used for discretization of second-order spatial derivatives are investigated in the context of Smoothed Particle Hydrodynamics. Three popular forms (i.e. "double summation", "second-order kernel derivation", and "difference scheme") are studied using one-dimensional unsteady heat conduction equation. To assess these schemes, transient response to a step function initial condition is considered. Due to parabolic nature of the heat equation, one can expect smooth and monotone solutions. It is shown, however in this paper, that regardless of the type of kernel function used and the size of smoothing radius, the double summation discretization form leads to non-physical oscillations which persist in the solution. Also, results show that when a second-order kernel derivative is used, a high-order kernel function shall be employed in such a way that the distance of inflection point from origin in the kernel function be less than the nearest particle distance. Otherwise, solutions may exhibit oscillations near discontinuities unlike the "difference scheme" which unconditionally produces monotone results.Keywords: Heat conduction, Meshfree methods, Smoothed ParticleHydrodynamics (SPH), Second-order derivatives.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30742330 Multi-Factor Optimization Method through Machine Learning in Building Envelope Design: Focusing on Perforated Metal Façade
Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim
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Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.
Keywords: Building envelope, machine learning, perforated metal, multi-factor optimization, façade.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12032329 Enhanced Interference Management Technique for Multi-Cell Multi-Antenna System
Authors: Simon E. Uguru, Victor E. Idigo, Obinna S. Oguejiofor, Naveed Nawaz
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As the deployment of the Fifth Generation (5G) mobile communication networks take shape all over the world, achieving spectral efficiency, energy efficiency, and dealing with interference are among the greatest challenges encountered so far. The aim of this study is to mitigate inter-cell interference (ICI) in a multi-cell multi-antenna system while maximizing the spectral efficiency of the system. In this study, a system model was devised that showed a miniature representation of a multi-cell multi-antenna system. Based on this system model, a convex optimization problem was formulated to maximize the spectral efficiency of the system while mitigating the ICI. This optimization problem was solved using CVX, which is a modeling system for constructing and solving discipline convex programs. The solutions to the optimization problem are sub-optimal coordinated beamformers. These coordinated beamformers direct each data to the served user equipments (UEs) in each cell without interference during downlink transmission, thereby maximizing the system-wide spectral efficiency.
Keywords: coordinated beamforming, convex optimization, inter-cell interference, multi-antenna, multi-cell, spectral efficiency
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4262328 Practical Design Procedures of 3D Reinforced Concrete Shear Wall-Frame Structure Based on Structural Optimization Method
Authors: H. Nikzad, S. Yoshitomi
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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.
Keywords: Structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12772327 Statistical Analysis of First Order Plus Dead-time System using Operational Matrix
Authors: Pham Luu Trung Duong, Moonyong Lee
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To increase precision and reliability of automatic control systems, we have to take into account of random factors affecting the control system. Thus, operational matrix technique is used for statistical analysis of first order plus time delay system with uniform random parameter. Examples with deterministic and stochastic disturbance are considered to demonstrate the validity of the method. Comparison with Monte Carlo method is made to show the computational effectiveness of the method.
Keywords: First order plus dead-time, Operational matrix, Statistical analysis, Walsh function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13512326 Numerical Optimization within Vector of Parameters Estimation in Volatility Models
Authors: J. Arneric, A. Rozga
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In this paper usefulness of quasi-Newton iteration procedure in parameters estimation of the conditional variance equation within BHHH algorithm is presented. Analytical solution of maximization of the likelihood function using first and second derivatives is too complex when the variance is time-varying. The advantage of BHHH algorithm in comparison to the other optimization algorithms is that requires no third derivatives with assured convergence. To simplify optimization procedure BHHH algorithm uses the approximation of the matrix of second derivatives according to information identity. However, parameters estimation in a/symmetric GARCH(1,1) model assuming normal distribution of returns is not that simple, i.e. it is difficult to solve it analytically. Maximum of the likelihood function can be founded by iteration procedure until no further increase can be found. Because the solutions of the numerical optimization are very sensitive to the initial values, GARCH(1,1) model starting parameters are defined. The number of iterations can be reduced using starting values close to the global maximum. Optimization procedure will be illustrated in framework of modeling volatility on daily basis of the most liquid stocks on Croatian capital market: Podravka stocks (food industry), Petrokemija stocks (fertilizer industry) and Ericsson Nikola Tesla stocks (information-s-communications industry).Keywords: Heteroscedasticity, Log-likelihood Maximization, Quasi-Newton iteration procedure, Volatility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26332325 Optimization of Protein Hydrolysate Production Process from Jatropha curcas Cake
Authors: Waraporn Apiwatanapiwat, Pilanee Vaithanomsat, Phanu Somkliang, Taweesiri Malapant
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This was the first document revealing the investigation of protein hydrolysate production optimization from J. curcas cake. Proximate analysis of raw material showed 18.98% protein, 5.31% ash, 8.52% moisture and 12.18% lipid. The appropriate protein hydrolysate production process began with grinding the J. curcas cake into small pieces. Then it was suspended in 2.5% sodium hydroxide solution with ratio between solution/ J. curcas cake at 80:1 (v/w). The hydrolysis reaction was controlled at temperature 50 °C in water bath for 45 minutes. After that, the supernatant (protein hydrolysate) was separated using centrifuge at 8000g for 30 minutes. The maximum yield of resulting protein hydrolysate was 73.27 % with 7.34% moisture, 71.69% total protein, 7.12% lipid, 2.49% ash. The product was also capable of well dissolving in water.Keywords: Production, protein hydrolysate, Jatropha curcas cake, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19402324 Optimization Based Obstacle Avoidance
Authors: R. Dariani, S. Schmidt, R. Kasper
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Based on a non-linear single track model which describes the dynamics of vehicle, an optimal path planning strategy is developed. Real time optimization is used to generate reference control values to allow leading the vehicle alongside a calculated lane which is optimal for different objectives such as energy consumption, run time, safety or comfort characteristics. Strict mathematic formulation of the autonomous driving allows taking decision on undefined situation such as lane change or obstacle avoidance. Based on position of the vehicle, lane situation and obstacle position, the optimization problem is reformulated in real-time to avoid the obstacle and any car crash.
Keywords: Autonomous driving, Obstacle avoidance, Optimal control, Path planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29962323 Ant Colony Optimization for Optimal Distributed Generation in Distribution Systems
Authors: I. A. Farhat
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The problem of optimal planning of multiple sources of distributed generation (DG) in distribution networks is treated in this paper using an improved Ant Colony Optimization algorithm (ACO). This objective of this problem is to determine the DG optimal size and location that in order to minimize the network real power losses. Considering the multiple sources of DG, both size and location are simultaneously optimized in a single run of the proposed ACO algorithm. The various practical constraints of the problem are taken into consideration by the problem formulation and the algorithm implementation. A radial power flow algorithm for distribution networks is adopted and applied to satisfy these constraints. To validate the proposed technique and demonstrate its effectiveness, the well-know 69-bus feeder standard test system is employed.cm.
Keywords: About Ant Colony Optimization (ACO), Distributed Generation (DG).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32642322 Deterministic Random Number Generator Algorithm for Cryptosystem Keys
Authors: Adi A. Maaita, Hamza A. A. Al_Sewadi
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One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced, or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfill Shannon’s principle of “confusion and diffusion”. ASCII code characters were utilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.Keywords: Cryptosystems, Information Security agreement, Key distribution, Random numbers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34152321 Solving Weighted Number of Operation Plus Processing Time Due-Date Assignment, Weighted Scheduling and Process Planning Integration Problem Using Genetic and Simulated Annealing Search Methods
Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun
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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.
Keywords: Process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15802320 High Level Characterization and Optimization of Switched-Current Sigma-Delta Modulators with VHDL-AMS
Authors: A. Fakhfakh, N. Ksentini, M. Loulou, N. Masmoudi, J. J. Charlot
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Today, design requirements are extending more and more from electronic (analogue and digital) to multidiscipline design. These current needs imply implementation of methodologies to make the CAD product reliable in order to improve time to market, study costs, reusability and reliability of the design process. This paper proposes a high level design approach applied for the characterization and the optimization of Switched-Current Sigma- Delta Modulators. It uses the new hardware description language VHDL-AMS to help the designers to optimize the characteristics of the modulator at a high level with a considerably reduced CPU time before passing to a transistor level characterization.Keywords: high level design, optimization, switched-Current Sigma-Delta Modulators, VHDL-AMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15052319 Impact of Ship Traffic to PM2.5 and Particle Number Concentrations in Three Port-Cities of the Adriatic/Ionian Area
Authors: Daniele Contini, Antonio Donateo, Andrea Gambaro, Athanasios Argiriou, Dimitrios Melas, Daniela Cesari, Anastasia Poupkou, Athanasios Karagiannidis, Apostolos Tsakis, Eva Merico, Rita Cesari, Adelaide Dinoi
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Emissions of atmospheric pollutants from ships and harbour activities are a growing concern at international level given their potential impacts on air quality and climate. These close-to-land emissions have potential impact on local communities in terms of air quality and health. Recent studies show that the impact of maritime traffic to atmospheric particulate matter concentrations in several coastal urban areas is comparable with the impact of road traffic of a medium size town. However, several different approaches have been used for these estimates making difficult a direct comparison of results. In this work, an integrated approach based on emission inventories and dedicated measurement campaigns has been applied to give a comparable estimate of the impact of maritime traffic to PM2.5 and particle number concentrations in three major harbours of the Adriatic/Ionian Seas. The influences of local meteorology and of the logistic layout of the harbours are discussed.
Keywords: Ship emissions, PM2.5, particle number concentrations, impact of shipping to atmospheric aerosol.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23842318 Solid State Fermentation of Cassava Peel with Trichoderma viride (ATCC 36316) for Protein Enrichment
Authors: Olufunke O. Ezekiel, Ogugua C. Aworh
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Solid state fermentation of cassava peel with emphasis on protein enrichment using Trichoderma viride was evaluated. The effect of five variables: moisture content, pH, particle size (p), nitrogen source and incubation temperature; on the true protein and total sugars of cassava peel was investigated. The optimum fermentation period was established to be 8 days. Total sugars were 5-fold higher at pH 6 relative to pH 4 and 7-fold higher when cassava peels were fermented at 30oC relative to 25oC as well as using ammonium sulfate as the nitrogen source relative to urea or a combination of both. Total sugars ranged between 123.21mg/g at 50% initial moisture content to 374mg/g at 60% and from 190.59mg/g with particle size range of 2.00>p>1.41mm to 310.10mg/g with 4.00>p>3.35mm.True protein ranged from 229.70 mg/g at pH 4 to 284.05 mg/g at pH 6; from 200.87 mg/g with urea as nitrogen source and to 254.50mg/g with ammonium sulfate; from 213.82mg/g at 50% initial moisture content to 254.50mg/g at 60% moisture content, from 205.75mg/g in cassava peel with 5.6>p> 4.75mm to 268.30 in cassava peel with particle size 4.00>p>3.35mm, from 207.57mg/g at 25oC to 254.50mg/g at 30oC Cassava peel with particle size 4.00>p>3.35 mm and initial moisture content of 60% at pH 6.0, 30oC incubation temperature with ammonium sulfate (10g N / kg substrate) was most suitable for protein enrichment with Trichoderma viride. Crude protein increased from 4.21 % in unfermented cassava peel samples to 10.43 % in fermented samples.
Keywords: Cassava peel, Solid state fermentation, Trichoderma viride, Total sugars, True protein.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33242317 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 35852316 Performance Evaluation of Data Mining Techniques for Predicting Software Reliability
Authors: Pradeep Kumar, Abdul Wahid
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Accurate software reliability prediction not only enables developers to improve the quality of software but also provides useful information to help them for planning valuable resources. This paper examines the performance of three well-known data mining techniques (CART, TreeNet and Random Forest) for predicting software reliability. We evaluate and compare the performance of proposed models with Cascade Correlation Neural Network (CCNN) using sixteen empirical databases from the Data and Analysis Center for Software. The goal of our study is to help project managers to concentrate their testing efforts to minimize the software failures in order to improve the reliability of the software systems. Two performance measures, Normalized Root Mean Squared Error (NRMSE) and Mean Absolute Errors (MAE), illustrate that CART model is accurate than the models predicted using Random Forest, TreeNet and CCNN in all datasets used in our study. Finally, we conclude that such methods can help in reliability prediction using real-life failure datasets.
Keywords: Classification, Cascade Correlation Neural Network, Random Forest, Software reliability, TreeNet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18242315 Characterization of Fabricated A 384.1-MgO Based Metal Matrix Composite and Optimization of Tensile Strength using Taguchi Techniques
Authors: Nripjit, Anand K Tyagi, Nirmal Singh
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The present work consecutively on synthesis and characterization of composites, Al/Al alloy A 384.1 as matrix in which the main ingredient as Al/Al-5% MgO alloy based metal matrix composite. As practical implications the low cost processing route for the fabrication of Al alloy A 384.1 and operational difficulties of presently available manufacturing processes based in liquid manipulation methods. As all new developments, complete understanding of the influence of processing variables upon the final quality of the product. And the composite is applied comprehensively to the acquaintance for achieving superiority of information concerning the specific heat measurement of a material through the aid of thermographs. Products are evaluated concerning relative particle size and mechanical behavior under tensile strength. Furthermore, Taguchi technique was employed to examine the experimental optimum results are achieved, owing to effectiveness of this approach.Keywords: MMC, Thermographs, Tensile strength, Taguchi technique, Optimal parameters
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16302314 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 9062313 Chemical Characterization of Submicron Aerosol in Kanpur Region: a Source Apportionment Study
Authors: A. Chakraborty, T. Gupta
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Several studies have shown the association between ambient particulate matter (PM) and adverse health effects and climate change, thus highlighting the need to limit the anthropogenic sources of PM. PM Exposure is commonly monitored as mass concentration of PM10 (particle aerodynamic diameter < 10μm) or PM2.5 (particle aerodynamic diameter < 2.5μm), although increasing toxicity with decreasing aerodynamic diameter has been reported due to increased surface area and enhanced chemical reactivity with other species. Additionally, the light scattering properties of PM increases with decreasing size. Hence, it is important to study the chemical characterization of finer fraction of the particulate matter and to identify their sources so that they can be controlled appropriately to a large extent at the sources before reaching to the receptors.Keywords: PM1, PCA, source apportionment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16392312 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 7822311 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 19622310 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 15422309 Vision Based Hand Gesture Recognition Using Generative and Discriminative Stochastic Models
Authors: Mahmoud Elmezain, Samar El-shinawy
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Many approaches to pattern recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the distribution of the image features. Generative and discriminative models have very different characteristics, as well as complementary strengths and weaknesses. In this paper, we study these models to recognize the patterns of alphabet characters (A-Z) and numbers (0-9). To handle isolated pattern, generative model as Hidden Markov Model (HMM) and discriminative models like Conditional Random Field (CRF), Hidden Conditional Random Field (HCRF) and Latent-Dynamic Conditional Random Field (LDCRF) with different number of window size are applied on extracted pattern features. The gesture recognition rate is improved initially as the window size increase, but degrades as window size increase further. Experimental results show that the LDCRF is the best in terms of results than CRF, HCRF and HMM at window size equal 4. Additionally, our results show that; an overall recognition rates are 91.52%, 95.28%, 96.94% and 98.05% for CRF, HCRF, HMM and LDCRF respectively.
Keywords: Statistical Pattern Recognition, Generative Model, Discriminative Model, Human Computer Interaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29122308 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 17442307 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 26662306 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 19992305 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 19962304 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 7252303 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 29292302 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 3278