Loading...
Search for: pso
0.016 seconds
Total 309 records

    A conflict resolution method for waste load reallocation in river systems

    , Article International Journal of Environmental Science and Technology ; Volume 16, Issue 1 , 2019 , Pages 79-88 ; 17351472 (ISSN) Aghasian, K ; Moridi, A ; Mirbagheri, A ; Abbaspour, M ; Sharif University of Technology
    Center for Environmental and Energy Research and Studies  2019
    Abstract
    Various urban, industrial, and agricultural pollutions discharge more than river self-purification potential damages river ecosystem and increases water treatment costs. As different decision-makers and stakeholders are involved in the water quality management in river systems, a new bankruptcy form of the game theory is used to resolve the existing conflict of interests related to waste load allocation in downstream river. The river restoration potential can allocate to the conflicting parties with respect to their claims, by using bankruptcy solution methods. In this research, dischargeable pollution loads to Karun River are determined by pollution sources in various scenarios using... 

    A computational method for optimal design of the multi-tower heliostat field considering heliostats interactions

    , Article Energy ; Volume 106 , 2016 , Pages 240-252 ; 03605442 (ISSN) Piroozmand, P ; Boroushaki, M ; Sharif University of Technology
    Elsevier Ltd 
    Abstract
    In multi-tower heliostat fields, although heliostats are capable of aiming at different receivers during the day, due to different orientations, neighboring heliostats might affect shading and blocking efficiency of each other reciprocally. In the proposed method of this paper, considering the mentioned effects and based on a group decision-making approach, each heliostat chooses the best receiver thus ensuring the highest possible instantaneous efficiency of the field. As a case study, this method is applied for the optimal design of a multi-tower field. Then, the field performance is simulated in a case where heliostats make decisions individually without considering the interactions.... 

    A comprehensive FE study for design of anchored wall systems for deep excavations

    , Article Tunnelling and Underground Space Technology ; Volume 122 , 2022 ; 08867798 (ISSN) Maleki, J ; Pak, A ; Yousefi, M ; Aghakhani, N ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    Anchored wall system is one of the common methods used for deep excavation stabilization adjacent to sensitive structures in urban areas. A key aspect of the stability analysis of deep excavations is the amount of deformations occurring on the facing wall and the adjacent structures. In this research, a large number of parametric studies considering all aspects of soil-structure interaction is carried out for different excavation geometries to find the optimal design, and the outcome is shown in the form of design tables and charts. Also, by a GA-PSO algorithm and using the large database obtained from the numerical simulations, a simple equation is developed that can predict the deflections... 

    A comparative study of optimization algorithms for wavefront shaping

    , Article Journal of Innovative Optical Health Sciences ; Volume 12, Issue 4 , 2019 ; 17935458 (ISSN) Fayyaz, Z ; Mohammadian, N ; Rahimi Tabar, M. R ; Manwar, R ; Avanaki, K ; Sharif University of Technology
    World Scientific Publishing Co. Pte Ltd  2019
    Abstract
    By manipulating the phase map of a wavefront of light using a spatial light modulator, the scattered light can be sharply focused on a specific target. Several iterative optimization algorithms for obtaining the optimum phase map have been explored. However, there has not been a comparative study on the performance of these algorithms. In this paper, six optimization algorithms for wavefront shaping including continuous sequential, partitioning algorithm, transmission matrix estimation method, particle swarm optimization, genetic algorithm (GA), and simulated annealing (SA) are discussed and compared based on their efficiency when introduced with various measurement noise levels  

    A combination of PSO and K-means methods to solve haplotype reconstruction problem

    , Article 2009 International Conference on Innovations in Information Technology, IIT '09, 15 December 2009 through 17 December 2009 ; 2009 , Pages 190-194 ; 9781424456987 (ISBN) Sharifian R, S ; Baharian, A ; Asgarian, E ; Rasooli, A ; Sharif University of Technology
    Abstract
    Disease association study is of great importance among various fields of study in bioinformatics. Computational methods happen to be advantageous specifically when experimental approaches fail to obtain accurate results. Haplotypes are believed to be the most responsible biological data for genetic diseases. In this paper, the problem of reconstructing haplotypes from error-containing SNP fragments is discussed For this purpose, two new methods have been proposed by a combination of k-means clustering and particle swarm optimization algorithm. The methods and their implementation results on real biological and simulation datasets are represented which shows that they outperform the methods... 

    Accurate prediction of kinematic viscosity of biodiesels and their blends with diesel fuels

    , Article JAOCS, Journal of the American Oil Chemists' Society ; Volume 97, Issue 10 , September , 2020 , Pages 1083-1094 Mehrizadeh, M ; Nikbin Fashkacheh, H ; Zand, N ; Najafi Marghmaleki, A ; Sharif University of Technology
    Wiley-Blackwell  2020
    Abstract
    Viscosity of mixtures of biodiesels (admixtures) and mixtures of biodiesel/diesel (blends) is a important parameter for determining their combustion behavior. There is no universal and general model for prediction of viscosity of these systems at different conditions. Hence, developing simple, accurate, and general models for prediction of viscosity of these systems is of great importance. In this work, three computer-based models named multilayer perceptron neural network (MLP-NN), radial basis function optimized by particle swarm optimization (PSO-RBF), and adaptive neuro fuzzy inference system optimized by hybrid approach (Hybrid-ANFIS) were developed for prediction of viscosity of blends... 

    A bi-objective inventory optimization model under inflation and discount using tuned Pareto-based algorithms: NSGA-II, NRGA, and MOPSO

    , Article Applied Soft Computing Journal ; Volume 43 , 2016 , Pages 57-72 ; 15684946 (ISSN) Mousavi, S. M ; Sadeghi, J ; Akhavan Niaki, S. T ; Tavana, M ; Sharif University of Technology
    Elsevier Ltd 
    Abstract
    This study presents a seasonal multi-product multi-period inventory control model with inventory costs obtained under inflation and all-unit discount policy. The products are delivered in boxes of known quantities and both backorder and lost-sale quantities are considered in case of shortage. The goal is to find a representative set of Pareto optimal solutions (including the ordering quantities) in different periods and to minimize both the total inventory cost (i.e. ordering, holding, shortage, and purchasing costs) and the total storage space, simultaneously. Three multi-objective optimization algorithms of non-dominated sorting genetic algorithm (NSGA-II), non-dominated ranked genetic... 

    A bi-objective hybrid optimization algorithm to reduce noise and data dimension in diabetes diagnosis using support vector machines

    , Article Expert Systems with Applications ; Volume 127 , 2019 , Pages 47-57 ; 09574174 (ISSN) Alirezaei, M ; Akhavan Niaki, S. T ; Akhavan Niaki, S. A ; Sharif University of Technology
    Elsevier Ltd  2019
    Abstract
    Diabetes mellitus is a medical condition examined by data miners for reasons such as significant health complications in affected people, the economic impact on healthcare networks, and so on. In order to find the main causes of this disease, researchers look into the patient's lifestyle, hereditary information, etc. The goal of data mining in this context is to find patterns that make early detection of the disease and proper treatment easier. Due to the high volume of data involved in therapeutic contexts and disease diagnosis, provision of the intended treatment method become almost impossible over a short period of time. This justifies the use of pre-processing techniques and data... 

    A 3D path planning algorithm based on PSO for autonomous UAVs navigation

    , Article 9th International Conference on Bioinspired Optimization Methods and Their Applications, BIOMA 2020, 19 November 2020 through 20 November 2020 ; Volume 12438 LNCS , 2020 , Pages 268-280 Mirshamsi, A ; Godio, S ; Nobakhti, A ; Primatesta, S ; Dovis, F ; Guglieri, G ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2020
    Abstract
    In this paper, a new three-dimensional path planning approach with obstacle avoidance for UAVs is proposed. The aim is to provide a computationally-fast on-board sub-optimal solution for collision-free path planning in static environments. The optimal 3D path is an NP (non-deterministic polynomial-time) hard problem which may be solved numerically by global optimization algorithms such as the Particle Swarm Optimization (PSO). Application of PSO to the 3D path planning class of problems faces typical challenges such slow convergence rate. It is shown that the performance may be improved markedly by implementing a novel parallel approach and incorporation of new termination conditions....