Search results for: Particle Swarms Optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2342

Search results for: Particle Swarms Optimization

2072 Comparative Study of Ant Colony and Genetic Algorithms for VLSI Circuit Partitioning

Authors: Sandeep Singh Gill, Rajeevan Chandel, Ashwani Chandel

Abstract:

This paper presents a comparative study of Ant Colony and Genetic Algorithms for VLSI circuit bi-partitioning. Ant colony optimization is an optimization method based on behaviour of social insects [27] whereas Genetic algorithm is an evolutionary optimization technique based on Darwinian Theory of natural evolution and its concept of survival of the fittest [19]. Both the methods are stochastic in nature and have been successfully applied to solve many Non Polynomial hard problems. Results obtained show that Genetic algorithms out perform Ant Colony optimization technique when tested on the VLSI circuit bi-partitioning problem.

Keywords: Partitioning, genetic algorithm, ant colony optimization, non-polynomial hard, netlist, mutation.

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2071 Analysis of Dust Particles in Snow Cover in the Surroundings of the City of Ostrava: Particle Size Distribution, Zeta Potential and Heavy Metal Content

Authors: Roman Marsalek

Abstract:

In this paper, snow samples containing dust particles from several sampling points around the city of Ostrava were analyzed. The pH values of sampled snow were measured and solid particles analyzed. Particle size, zeta potential and content of selected heavy metals were determined in solid particles. The pH values of most samples lay in the slightly acid region. Mean values of particle size ranged from 290.5 to 620.5 nm. Zeta potential values varied between -5 and -26.5 mV. The following heavy metal concentration ranges were found: copper 0.08-0.75 mg/g, lead 0.05-0.9 mg/g, manganese 0.45-5.9 mg/g and iron 25.7-280.46 mg/g. The highest values of copper and lead were found in the vicinity of busy crossroads, and on the contrary, the highest levels of manganese and iron were detected close to a large steelworks. The proportion between pH values, zeta potentials, particle sizes and heavy metal contents was established. Zeta potential decreased with rising pH values and, simultaneously, heavy metal content in solid particles increased. At the same time, higher metal content corresponded to lower particle size.

Keywords: Dust, snow, zeta potential, particles size distribution, heavy metals.

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2070 Tools for Analysis and Optimization of Standalone Green Microgrids

Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

Abstract:

Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.

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2069 Cloud Monitoring and Performance Optimization Ensuring High Availability and Security

Authors: Inayat Ur Rehman, Georgia Sakellari

Abstract:

Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: Cloud computing, cloud monitoring, performance optimization, high availability.

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2068 Optimizing the Design of Radial/Axial PMSM and SRM used for Powered Wheel-Chairs

Authors: D. Fodorean, D.C. Popa, F. Jurca, M. Ruba

Abstract:

the paper presents the optimization results for several electrical machines dedicated for powered electric wheel-chairs. The optimization, using the Hook-Jeeves algorithm, was employed based on a design approach which takes into consideration the road conditions. Also, through numerical simulations (based on finite element method), the analytical approach was validated. The optimization approach gave satisfactory results and the best suited variant was chosen for the motorization of the wheel-chair.

Keywords: electrical machines, numerical validation, optimization, electric wheel chair.

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2067 Dynamical Characteristics of Interaction between Water Droplet and Aerosol Particle in Dedusting Technology

Authors: Ding Jue, Li Jiahua, Lei Zhidi, Weng Peifen, Li Xiaowei

Abstract:

With the rapid development of national modern industry, people begin to pay attention to environmental pollution and harm caused by industrial dust. Based on above, a numerical study on the dedusting technology of industrial environment was conducted. The dynamic models of multicomponent particles collision and coagulation, breakage and deposition are developed, and the interaction of water droplet and aerosol particle in 2-Dimension flow field was researched by Eulerian-Lagrangian method and Multi-Monte Carlo method. The effects of the droplet scale, movement speed of droplet and the flow field structure on scavenging efficiency were analyzed. The results show that under the certain condition, 30μm of droplet has the best scavenging efficiency. At the initial speed 1m/s of droplets, droplets and aerosol particles have more time to interact, so it has a better scavenging efficiency for the particle.

Keywords: Water droplet, aerosol particle, collision and coagulation, multi-Monte Carlo method.

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2066 A Proposed Optimized and Efficient Intrusion Detection System for Wireless Sensor Network

Authors: Abdulaziz Alsadhan, Naveed Khan

Abstract:

In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

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2065 Modeling of Dielectric Heating in Radio- Frequency Applicator Optimized for Uniform Temperature by Means of Genetic Algorithms

Authors: Camelia Petrescu, Lavinia Ferariu

Abstract:

The paper presents an optimization study based on genetic algorithms (GA-s) for a radio-frequency applicator used in heating dielectric band products. The weakly coupled electro-thermal problem is analyzed using 2D-FEM. The design variables in the optimization process are: the voltage of a supplementary “guard" electrode and six geometric parameters of the applicator. Two objective functions are used: temperature uniformity and total active power absorbed by the dielectric. Both mono-objective and multiobjective formulations are implemented in GA optimization.

Keywords: Dielectric heating, genetic algorithms, optimization, RF applicators.

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2064 Cleaning Performance of High-Frequency, High-Intensity 360 kHz Frequency Operating in Thickness Mode Transducers

Authors: R. Vetrimurugan, Terry Lim, M. J. Goodson, R. Nagarajan

Abstract:

This study investigates the cleaning performance of high intensity 360 kHz frequency on removal of nano-dimensional and sub-micron particles from various surfaces, uniformity of the cleaning tank and run to run variation of cleaning process. The uniformity of the cleaning tank was measured by two different methods i.e. 1. ppbTM meter and 2. Liquid Particle Counting (LPC) technique. The result indicates that the energy was distributed more uniformly throughout the entire cleaning vessel even at the corners and edges of the tank when megasonic sweeping technology is applied. The result also shows that rinsing the parts with 360 kHz frequency at final rinse gives lower particle counts, hence higher cleaning efficiency as compared to other frequencies. When megasonic sweeping technology is applied each piezoelectric transducers will operate at their optimum resonant frequency and generates stronger acoustic cavitational force and higher acoustic streaming velocity. These combined forces are helping to enhance the particle removal and at the same time improve the overall cleaning performance. The multiple extractions study was also carried out for various frequencies to measure the cleaning potential and asymptote value.

Keywords: Power distribution, megasonic sweeping, thickness mode transducers, cavitation intensity, particle removal, laser particle counting, nano, submicron.

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2063 The Synthetic T2 Quality Control Chart and its Multi-Objective Optimization

Authors: Francisco Aparisi, Marco A. de Luna

Abstract:

In some real applications of Statistical Process Control it is necessary to design a control chart to not detect small process shifts, but keeping a good performance to detect moderate and large shifts in the quality. In this work we develop a new quality control chart, the synthetic T2 control chart, that can be designed to cope with this objective. A multi-objective optimization is carried out employing Genetic Algorithms, finding the Pareto-optimal front of non-dominated solutions for this optimization problem.

Keywords: Multi-objective optimization, Quality Control, SPC, Synthetic T2 control chart.

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2062 Effect of Cyclotron Resonance Frequencies in Particles Due to AC and DC Electromagnetic Fields

Authors: Malka N. Halgamuge, Chathurika D. Abeyratne, Priyan Mendis

Abstract:

A fundamental model consisting of charged particles moving in free space exposed to alternating and direct current (ACDC) electromagnetic fields is analyzed. Effects of charged particles initial position and initial velocity to cyclotron resonance frequency are observed. Strong effects are observed revealing that effects of electric and magnetic fields on a charged particle in free space varies with the initial conditions. This indicates the frequency where maximum displacement occur can be changed. At this frequency the amplitude of oscillation of the particle displacement becomes unbounded.

Keywords: Cyclotron resonance, electromagnetic fields, particle displacement

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2061 A Numerical Study on Electrophoresis of a Soft Particle with Charged Core Coated with Polyelectrolyte Layer

Authors: Partha Sarathi Majee, S. Bhattacharyya

Abstract:

Migration of a core-shell soft particle under the influence of an external electric field in an electrolyte solution is studied numerically. The soft particle is coated with a positively charged polyelectrolyte layer (PEL) and the rigid core is having a uniform surface charge density. The Darcy-Brinkman extended Navier-Stokes equations are solved for the motion of the ionized fluid, the non-linear Nernst-Planck equations for the ion transport and the Poisson equation for the electric potential. A pressure correction based iterative algorithm is adopted for numerical computations. The effects of convection on double layer polarization (DLP) and diffusion dominated counter ions penetration are investigated for a wide range of Debye layer thickness, PEL fixed surface charge density, and permeability of the PEL. Our results show that when the Debye layer is in order of the particle size, the DLP effect is significant and produces a reduction in electrophoretic mobility. However, the double layer polarization effect is negligible for a thin Debye layer or low permeable cases. The point of zero mobility and the existence of mobility reversal depending on the electrolyte concentration are also presented.

Keywords: Debye length, double layer polarization, electrophoresis, mobility reversal, soft particle.

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2060 Rapid Expansion Supercritical Solution (RESS) Carbon Dioxide as an Environmental Friendly Method for Ginger Rhizome Solid Oil Particles Formation

Authors: N. A. Zainuddin, I. Norhuda, I. S. Adeib, A. N. Mustapa, S. H. Sarijo

Abstract:

Recently, RESS (Rapid Expansion Supercritical Solution) method has been used by researchers to produce fine particles for pharmaceutical drug substances. Since RESS technology acknowledges a lot of benefits compare to conventional method of ginger extraction, it is suggested to use this method to explore particle formation of bioactive compound from powder ginger. The objective of this research is to produce direct solid oil particles formation from ginger rhizome which contains valuable compounds by using RESS-CO2 process. RESS experiments were carried using extraction pressure of 3000, 4000, 5000, 6000 and 7000psi and at different extraction temperature of 40, 45, 50, 55, 60, 65 and 70°C for 40 minutes extraction time and contant flowrate (24ml/min). From the studies conducted, it was found that at extraction pressure 5000psi and temperature 40°C, the smallest particle size obtained was 2.22μm on 99 % reduction from the original size of 370μm.

Keywords: Particle size, RESS, solid oil particle, supercritical carbon dioxide.

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2059 Kinetic Theory Based CFD Modeling of Particulate Flows in Horizontal Pipes

Authors: Pandaba Patro, Brundaban Patro

Abstract:

The numerical simulation of fully developed gas–solid flow in a horizontal pipe is done using the eulerian-eulerian approach, also known as two fluids modeling as both phases are treated as continuum and inter-penetrating continua. The solid phase stresses are modeled using kinetic theory of granular flow (KTGF). The computed results for velocity profiles and pressure drop are compared with the experimental data. We observe that the convection and diffusion terms in the granular temperature cannot be neglected in gas solid flow simulation along a horizontal pipe. The particle-wall collision and lift also play important role in eulerian modeling. We also investigated the effect of flow parameters like gas velocity, particle properties and particle loading on pressure drop prediction in different pipe diameters. Pressure drop increases with gas velocity and particle loading. The gas velocity has the same effect ((proportional toU2 ) as single phase flow on pressure drop prediction. With respect to particle diameter, pressure drop first increases, reaches a peak and then decreases. The peak is a strong function of pipe bore.

Keywords: CFD, Eulerian modeling, gas solid flow, KTGF.

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2058 Mechanical Properties of Particle Boards from Maize Cob and Urea-Formaldehyde Resin

Authors: A. Danladi, I. O. Patrick

Abstract:

Particle boards were prepared from Maize cob (MC) and urea-formaldehyde resin (UFR) on compression moulding machine. The amount of MC was varied from 50-120g while 30g of UFR was kept constant. Some mechanical properties of the particle boards were tested using the standard ASM methods. The results show that as the MC content increased from 50- 120g in 30g UFR, the hardness increased from about 6.89 x 102 to7.51 x 102MPa. Impact strength decreased from 3.3x 10-2 to 0.45 x 10-2J/M2, while tensile strength initially increased from 2.63 x 102 to 3.14 x 102 MPa as the MC increased from 50 to 60g in 30g UFR, thereafter, it decreased to about 1.35 x 102MPa at 120g in 30g content.

Keywords: Hardness, Impact strength, Maize cob, Tensile strength and Urea-formaldehyde resin.

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2057 Performance Comparison of Prim’s and Ant Colony Optimization Algorithm to Select Shortest Path in Case of Link Failure

Authors: Rimmy Yadav, Avtar Singh

Abstract:

Ant Colony Optimization (ACO) is a promising modern approach to the unused combinatorial optimization. Here ACO is applied to finding the shortest during communication link failure. In this paper, the performances of the prim’s and ACO algorithm are made. By comparing the time complexity and program execution time as set of parameters, we demonstrate the pleasant performance of ACO in finding excellent solution to finding shortest path during communication link failure.

Keywords: Ant colony optimization, link failure, prim’s algorithm.

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2056 Combined Simulated Annealing and Genetic Algorithm to Solve Optimization Problems

Authors: Younis R. Elhaddad

Abstract:

Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative states. However, there are also significant differences between them. The GA mechanism is parallel on a set of solutions and exchanges information using the crossover operation. SA works on a single solution at a time. In this work SA and GA are combined using new technique in order to overcome the disadvantages' of both algorithms.

Keywords: Genetic Algorithm, Optimization problems, Simulated Annealing, Traveling Salesman Problem

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2055 Dynamic Voltage Stability Estimation using Particle Filter

Authors: Osea Zebua, Norikazu Ikoma, Hiroshi Maeda

Abstract:

Estimation of voltage stability based on optimal filtering method is presented. PV curve is used as a tool for voltage stability analysis. Dynamic voltage stability estimation is done by using particle filter method. Optimum value (nose point) of PV curve can be estimated by estimating parameter of PV curve equation optimal value represents critical voltage and condition at specified point of measurement. Voltage stability is then estimated by analyzing loading margin condition c stimating equation. This maximum loading ecified dynamically.

Keywords: normalized PV curve, optimal filtering method particle filter, voltage stability.

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2054 Cognitive Virtual Exploration for Optimization Model Reduction

Authors: Livier Serna, Xavier Fischer, Fouad Bennis

Abstract:

In this paper, a decision aid method for preoptimization is presented. The method is called “negotiation", and it is based on the identification, formulation, modeling and use of indicators defined as “negotiation indicators". These negotiation indicators are used to explore the solution space by means of a classbased approach. The classes are subdomains for the negotiation indicators domain. They represent equivalent cognitive solutions in terms of the negotiation indictors being used. By this method, we reduced the size of the solution space and the criteria, thus aiding the optimization methods. We present an example to show the method.

Keywords: Optimization Model Reduction, Pre-Optimization, Negotiation Process, Class-Making, Cognition Based VirtualExploration.

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2053 Rational Structure of Panel with Curved Plywood Ribs

Authors: Janis Šliseris, Karlis Rocens

Abstract:

Optimization of rational geometrical and mechanical parameters of panel with curved plywood ribs is considered in this paper. The panel consists of cylindrical plywood ribs manufactured from Finish plywood, upper and bottom plywood flange, stiffness diaphragms. Panel is filled with foam. Minimal ratio of structure self weight and load that could be applied to structure is considered as rationality criteria. Optimization is done, by using classical beam theory without nonlinearities. Optimization of discreet design variables is done by Genetic algorithm.

Keywords: Curved plywood ribs, genetic algorithm, rationalparameters of ribbed panel, structure optimization.

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2052 Strategy for Optimal Configuration Design of Existing Structures by Topology and Shape Optimization Tools

Authors: Waqas Saleem, Fan Yuqing

Abstract:

A strategy is implemented to find the improved configuration design of an existing aircraft structure by executing topology and shape optimizations. Structural analysis of the Initial Design Space is performed in ANSYS under the loads pertinent to operating and ground conditions. By using the FEA results and data, an initial optimized layout configuration is attained by exploiting nonparametric topology optimization in TOSCA software. Topological optimized surfaces are then smoothened and imported in ANSYS to develop the geometrical features. Nodes at the critical locations of resulting voids are selected for sketching rough profiles. Rough profiles are further refined and CAD feasible geometric features are generated. The modified model is then analyzed under the same loadings and constraints as defined for topology optimization. Shape at the peak stress concentration areas are further optimized by exploiting the shape optimization in TOSCA.shape module. The harmonized stressed model with the modified surfaces is then imported in CATIA to develop the final design.

Keywords: Structural optimization, Topology optimization, Shape optimization, Tail fin

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2051 Thermodynamic Optimization of Turboshaft Engine using Multi-Objective Genetic Algorithm

Authors: S. Farahat, E. Khorasani Nejad, S. M. Hoseini Sarvari

Abstract:

In this paper multi-objective genetic algorithms are employed for Pareto approach optimization of ideal Turboshaft engines. In the multi-objective optimization a number of conflicting objective functions are to be optimized simultaneously. The important objective functions that have been considered for optimization are specific thrust (F/m& 0), specific fuel consumption ( P S ), output shaft power 0 (& /&) shaft W m and overall efficiency( ) O η . These objectives are usually conflicting with each other. The design variables consist of thermodynamic parameters (compressor pressure ratio, turbine temperature ratio and Mach number). At the first stage single objective optimization has been investigated and the method of NSGA-II has been used for multiobjective optimization. Optimization procedures are performed for two and four objective functions and the results are compared for ideal Turboshaft engine. In order to investigate the optimal thermodynamic behavior of two objectives, different set, each including two objectives of output parameters, are considered individually. For each set Pareto front are depicted. The sets of selected decision variables based on this Pareto front, will cause the best possible combination of corresponding objective functions. There is no superiority for the points on the Pareto front figure, but they are superior to any other point. In the case of four objective optimization the results are given in tables.

Keywords: Multi-objective, Genetic algorithm, Turboshaft Engine.

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2050 Engineering Optimization Using Two-Stage Differential Evolution

Authors: K. Y. Tseng, C. Y. Wu

Abstract:

This paper employs a heuristic algorithm to solve engineering problems including truss structure optimization and optimal chiller loading (OCL) problems. Two different type algorithms, real-valued differential evolution (DE) and modified binary differential evolution (MBDE), are successfully integrated and then can obtain better performance in solving engineering problems. In order to demonstrate the performance of the proposed algorithm, this study adopts each one testing case of truss structure optimization and OCL problems to compare the results of other heuristic optimization methods. The result indicates that the proposed algorithm can obtain similar or better solution in comparing with previous studies.

Keywords: Differential evolution, truss structure optimization, optimal chiller loading, modified binary differential evolution.

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2049 Experimental Modal Analysis and Model Validation of Antenna Structures

Authors: B.R. Potgieter, G. Venter

Abstract:

Numerical design optimization is a powerful tool that can be used by engineers during any stage of the design process. There are many different applications for structural optimization. A specific application that will be discussed in the following paper is experimental data matching. Data obtained through tests on a physical structure will be matched with data from a numerical model of that same structure. The data of interest will be the dynamic characteristics of an antenna structure focusing on the mode shapes and modal frequencies. The structure used was a scaled and simplified model of the Karoo Array Telescope-7 (KAT-7) antenna structure. This kind of data matching is a complex and difficult task. This paper discusses how optimization can assist an engineer during the process of correlating a finite element model with vibration test data.

Keywords: Finite Element Model (FEM), Karoo Array Telescope(KAT-7), modal frequencies, mode shapes, optimization, shape optimization, size optimization, vibration tests

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2048 Preparation of Porous Carbon Particles using a Spray-Drying Method with Colloidal Template

Authors: Yutaka Kisakibaru, AsepBayu Dani Nandiyanto, Ratna Balgis, Takashi Ogi, Kikuo Okuyama

Abstract:

spherical porous carbon particles with controllable porosity with a mean size of 2.5m have been prepared using a spray drying method with organic particle colloidal template. As a precursor, a mixing solution of carbon nanopowder and polystyrene (PS) particles as a template was used. The result showed that the particles with a good porous structure could be obtained. The pore size and shape (spherical) were identical to the initial template, giving a potential way for further developments. The control of particle porosity was also possible and reported in this paper, in which this control could be achieved by means of PS concentration.

Keywords: Porous structure particle; Carbon nanoparticles; Catalyst; Spray-drying method.

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2047 Purity Monitor Studies in Medium Liquid Argon TPC

Authors: I. Badhrees

Abstract:

This paper is an attempt to describe some of the results that had been found through a journey of study in the field of particle physics. This study consists of two parts, one about the measurement of the cross section of the decay of the Z particle in two electrons, and the other deals with the measurement of the cross section of the multi-photon absorption process using a beam of Laser in the Liquid Argon Time Projection Chamber.

The first part of the paper concerns the results based on the analysis of a data sample containing 8120 ee candidates to reconstruct the mass of the Z particle for each event where each event has an ee pair with PT(e) > 20GeV, and η(e) < 2.5. Monte Carlo templates of the reconstructed Z particle were produced as a function of the Z mass scale. The distribution of the reconstructed Z mass in the data was compared to the Monte Carlo templates, where the total cross section is calculated to be equal to 1432pb.

The second part concerns the Liquid Argon Time Projection Chamber, LAr TPC, the results of the interaction of the UV Laser, Nd-YAG with λ= 266mm, with LAr and through the study of the multi-photon ionization process as a part of the R&D at Bern University. The main result of this study was the cross section of the process of the multi-photon ionization process of the LAr, σe = 1.24±0.10stat±0.30sys.10 -56cm4.

Keywords: ATLAS, CERN, KACST, LArTPC, Particle Physics.

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2046 Chemical Reaction Algorithm for Expectation Maximization Clustering

Authors: Li Ni, Pen ManMan, Li KenLi

Abstract:

Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: Chemical reaction optimization, expectation maximization, initial, objective function clustering.

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2045 Performance Analysis of MATLAB Solvers in the Case of a Quadratic Programming Generation Scheduling Optimization Problem

Authors: Dávid Csercsik, Péter Kádár

Abstract:

In the case of the proposed method, the problem is parallelized by considering multiple possible mode of operation profiles, which determine the range in which the generators operate in each period. For each of these profiles, the optimization is carried out independently, and the best resulting dispatch is chosen. For each such profile, the resulting problem is a quadratic programming (QP) problem with a potentially negative definite Q quadratic term, and constraints depending on the actual operation profile. In this paper we analyze the performance of available MATLAB optimization methods and solvers for the corresponding QP.

Keywords: Economic dispatch, optimization, quadratic programming, MATLAB.

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2044 Formulation and ex vivo Evaluation of Solid Lipid Nanoparticles (SLNS) Based Hydrogel for Intranasal Drug Delivery

Authors: Pramod Jagtap, Kisan Jadhav, Neha Dand

Abstract:

Risperidone (RISP) is an antipsychotic agent and has low water solubility and nontargeted delivery results in numerous side effects. Hence, an attempt was made to develop SLNs hydrogel for intranasal delivery of RISP to achieve maximum bioavailability and reduction of side effects. RISP loaded SLNs composed of 1.65% (w/v) lipid mass were produced by high shear homogenization (HSH) coupled ultrasound (US) method using glycerylmonostearate (GMS) or Imwitor 900K (solid lipid). The particles were loaded with 0.2% (w/v) of the RISP & surface-tailored with a 2.02% (w/v) non-ionic surfactant Tween® 80. Optimization was done using 32 factorial design using Design Expert® software. The prepared SLNs dispersion incorporated into Polycarbophil AA1 hydrogel (0.5% w/v). The final gel formulation was evaluated for entrapment efficiency, particle size, rheological properties, X ray diffraction, in vitro diffusion, ex vivo permeation using sheep nasal mucosa and histopathological studies for nasocilliary toxicity. The entrapment efficiency of optimized SLNs was found to be 76 ± 2%, polydispersity index <0.3., particle size 278 ± 5 nm. This optimized batch was incorporated into hydrogel. The pH was found to be 6.4 ± 0.14. The rheological behaviour of hydrogel formulation revealed no thixotropic behaviour. In histopathology study, there was no nasocilliary toxicity observed in nasal mucosa after ex vivo permeation. X-ray diffraction data shows drug was in amorphous form. Ex vivo permeation study shows controlled release profile of drug.

Keywords: Ex vivo, particle size, risperidone, solid lipid nanoparticles.

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2043 Slime Mould Optimization Algorithms for Optimal Distributed Generation Integration in Distribution Electrical Network

Authors: F. Fissou Amigue, S. Ndjakomo Essiane, S. Pérabi Ngoffé, G. Abessolo Ondoa, G. Mengata Mengounou, T. P. Nna Nna

Abstract:

This document proposes a method for determining the optimal point of integration of distributed generation (DG) in distribution grid. Slime mould optimization is applied to determine best node in case of one and two injection point. Problem has been modeled as an optimization problem where the objective is to minimize joule loses and main constraint is to regulate voltage in each point. The proposed method has been implemented in MATLAB and applied in IEEE network 33 and 69 nodes. Comparing results obtained with other algorithms showed that slime mould optimization algorithms (SMOA) have the best reduction of power losses and good amelioration of voltage profile.

Keywords: Optimization, distributed generation, integration, slime mould algorithm.

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