Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3702

Search results for: function analysis

3702 Roll of Membership functions in Fuzzy Logic for Prediction of Shoot Length of Mustard Plant Based on Residual Analysis

Authors: Satyendra Nath Mandal, J. Pal Choudhury, Dilip De, S. R. Bhadra Chaudhuri

Abstract:

The selection for plantation of a particular type of mustard plant depending on its productivity (pod yield) at the stage of maturity. The growth of mustard plant dependent on some parameters of that plant, these are shoot length, number of leaves, number of roots and roots length etc. As the plant is growing, some leaves may be fall down and some new leaves may come, so it can not gives the idea to develop the relationship with the seeds weight at mature stage of that plant. It is not possible to find the number of roots and root length of mustard plant at growing stage that will be harmful of this plant as roots goes deeper to deeper inside the land. Only the value of shoot length which increases in course of time can be measured at different time instances. Weather parameters are maximum and minimum humidity, rain fall, maximum and minimum temperature may effect the growth of the plant. The parameters of pollution, water, soil, distance and crop management may be dominant factors of growth of plant and its productivity. Considering all parameters, the growth of the plant is very uncertain, fuzzy environment can be considered for the prediction of shoot length at maturity of the plant. Fuzzification plays a greater role for fuzzification of data, which is based on certain membership functions. Here an effort has been made to fuzzify the original data based on gaussian function, triangular function, s-function, Trapezoidal and L –function. After that all fuzzified data are defuzzified to get normal form. Finally the error analysis (calculation of forecasting error and average error) indicates the membership function appropriate for fuzzification of data and use to predict the shoot length at maturity. The result is also verified using residual (Absolute Residual, Maximum of Absolute Residual, Mean Absolute Residual, Mean of Mean Absolute Residual, Median of Absolute Residual and Standard Deviation) analysis.

Keywords: Fuzzification, defuzzification, gaussian function, triangular function, trapezoidal function, s-function, , membership function, residual analysis.

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3701 Application of Subversion Analysis in the Search for the Causes of Cracking in a Marine Engine Injector Nozzle

Authors: Leszek Chybowski, Artur Bejger, Katarzyna Gawdzińska

Abstract:

Subversion analysis is a tool used in the TRIZ (Theory of Inventive Problem Solving) methodology. This article introduces the history and describes the process of subversion analysis, as well as function analysis and analysis of the resources, used at the design stage when generating possible undesirable situations. The article charts the course of subversion analysis when applied to a fuel injection nozzle of a marine engine. The work describes the fuel injector nozzle as a technological system and presents principles of analysis for the causes of a cracked tip of the nozzle body. The system is modelled with functional analysis. A search for potential causes of the damage is undertaken and a cause-and-effect analysis for various hypotheses concerning the damage is drawn up. The importance of particular hypotheses is evaluated and the most likely causes of damage identified.

Keywords: Complex technical system, fuel injector, function analysis, importance analysis, resource analysis, sabotage analysis, subversion analysis, TRIZ.

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3700 Analysis of Train Passenger Seat Using Ergonomic Function Deployment Method

Authors: Robertoes K. K. Wibowo, Siswoyo Soekarno, Irma Puspitasari

Abstract:

Indonesian people use trains for their transportation, especially they use economy class train transportation because it is cheaper and has a more precise schedule than any other ground transportation. Nevertheless, the economy class passenger seat raises some inconvenience issues for passengers. This is due to the design of the chair on the economic class of trains that did not adjusted to the shape of anthropometry of Indonesian people. Thus, research needs to be conducted on the design of the seats in the economic class of trains. The purpose of this research is to make the design of economy class passenger seats ergonomic. This research method uses questionnaires and anthropometry measurements. The data obtained is processed using House of Quality of Ergonomic Function Development. From the results of analysis and data processing were obtained important changes from the original design. Ergonomic chair design according to the analysis is a stainless steel frame, seat height 390 mm, with a seat width for each passenger of 400 mm and a depth of 400 mm. Design of the backrest has a height of 840 mm, width of 430 mm and length of 300 mm that can move at the angle of 105-115 degrees. The width of the footrest is 42 mm and 400 mm length. The thickness of the seat cushion is 100 mm.

Keywords: Chair, ergonomics, function development, train passenger.

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3699 An Extension of the Kratzel Function and Associated Inverse Gaussian Probability Distribution Occurring in Reliability Theory

Authors: R. K. Saxena, Ravi Saxena

Abstract:

In view of their importance and usefulness in reliability theory and probability distributions, several generalizations of the inverse Gaussian distribution and the Krtzel function are investigated in recent years. This has motivated the authors to introduce and study a new generalization of the inverse Gaussian distribution and the Krtzel function associated with a product of a Bessel function of the third kind )(zKQ and a Z - Fox-Wright generalized hyper geometric function introduced in this paper. The introduced function turns out to be a unified gamma-type function. Its incomplete forms are also discussed. Several properties of this gamma-type function are obtained. By means of this generalized function, we introduce a generalization of inverse Gaussian distribution, which is useful in reliability analysis, diffusion processes, and radio techniques etc. The inverse Gaussian distribution thus introduced also provides a generalization of the Krtzel function. Some basic statistical functions associated with this probability density function, such as moments, the Mellin transform, the moment generating function, the hazard rate function, and the mean residue life function are also obtained.KeywordsFox-Wright function, Inverse Gaussian distribution, Krtzel function & Bessel function of the third kind.

Keywords: Fox-Wright function, Inverse Gaussian distribution, Krtzel function & Bessel function of the third kind.

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3698 Blind Source Separation Using Modified Gaussian FastICA

Authors: V. K. Ananthashayana, Jyothirmayi M.

Abstract:

This paper addresses the problem of source separation in images. We propose a FastICA algorithm employing a modified Gaussian contrast function for the Blind Source Separation. Experimental result shows that the proposed Modified Gaussian FastICA is effectively used for Blind Source Separation to obtain better quality images. In this paper, a comparative study has been made with other popular existing algorithms. The peak signal to noise ratio (PSNR) and improved signal to noise ratio (ISNR) are used as metrics for evaluating the quality of images. The ICA metric Amari error is also used to measure the quality of separation.

Keywords: Amari error, Blind Source Separation, Contrast function, Gaussian function, Independent Component Analysis.

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3697 Evaluation on Recent Committed Crypt Analysis Hash Function

Authors: A. Arul Lawrence Selvakumar, C. Suresh Ganandhas

Abstract:

This paper describes the study of cryptographic hash functions, one of the most important classes of primitives used in recent techniques in cryptography. The main aim is the development of recent crypt analysis hash function. We present different approaches to defining security properties more formally and present basic attack on hash function. We recall Merkle-Damgard security properties of iterated hash function. The Main aim of this paper is the development of recent techniques applicable to crypt Analysis hash function, mainly from SHA family. Recent proposed attacks an MD5 & SHA motivate a new hash function design. It is designed not only to have higher security but also to be faster than SHA-256. The performance of the new hash function is at least 30% better than that of SHA-256 in software. And it is secure against any known cryptographic attacks on hash functions.

Keywords: Crypt Analysis, cryptographic.

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3696 Face Recognition using Radial Basis Function Network based on LDA

Authors: Byung-Joo Oh

Abstract:

This paper describes a method to improve the robustness of a face recognition system based on the combination of two compensating classifiers. The face images are preprocessed by the appearance-based statistical approaches such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). LDA features of the face image are taken as the input of the Radial Basis Function Network (RBFN). The proposed approach has been tested on the ORL database. The experimental results show that the LDA+RBFN algorithm has achieved a recognition rate of 93.5%

Keywords: Face recognition, linear discriminant analysis, radial basis function network.

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3695 Meta Model for Optimum Design Objective Function of Steel Frames Subjected to Seismic Loads

Authors: Salah R. Al Zaidee, Ali S. Mahdi

Abstract:

Except for simple problems of statically determinate structures, optimum design problems in structural engineering have implicit objective functions where structural analysis and design are essential within each searching loop. With these implicit functions, the structural engineer is usually enforced to write his/her own computer code for analysis, design, and searching for optimum design among many feasible candidates and cannot take advantage of available software for structural analysis, design, and searching for the optimum solution. The meta-model is a regression model used to transform an implicit objective function into objective one and leads in turn to decouple the structural analysis and design processes from the optimum searching process. With the meta-model, well-known software for structural analysis and design can be used in sequence with optimum searching software. In this paper, the meta-model has been used to develop an explicit objective function for plane steel frames subjected to dead, live, and seismic forces. Frame topology is assumed as predefined based on architectural and functional requirements. Columns and beams sections and different connections details are the main design variables in this study. Columns and beams are grouped to reduce the number of design variables and to make the problem similar to that adopted in engineering practice. Data for the implicit objective function have been generated based on analysis and assessment for many design proposals with CSI SAP software. These data have been used later in SPSS software to develop a pure quadratic nonlinear regression model for the explicit objective function. Good correlations with a coefficient, R2, in the range from 0.88 to 0.99 have been noted between the original implicit functions and the corresponding explicit functions generated with meta-model.

Keywords: Meta-modal, objective function, steel frames, seismic analysis, design.

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3694 Inverse Heat Conduction Analysis of Cooling on Run Out Tables

Authors: M. S. Gadala, Khaled Ahmed, Elasadig Mahdi

Abstract:

In this paper, we introduced a gradient-based inverse solver to obtain the missing boundary conditions based on the readings of internal thermocouples. The results show that the method is very sensitive to measurement errors, and becomes unstable when small time steps are used. The artificial neural networks are shown to be capable of capturing the whole thermal history on the run-out table, but are not very effective in restoring the detailed behavior of the boundary conditions. Also, they behave poorly in nonlinear cases and where the boundary condition profile is different. GA and PSO are more effective in finding a detailed representation of the time-varying boundary conditions, as well as in nonlinear cases. However, their convergence takes longer. A variation of the basic PSO, called CRPSO, showed the best performance among the three versions. Also, PSO proved to be effective in handling noisy data, especially when its performance parameters were tuned. An increase in the self-confidence parameter was also found to be effective, as it increased the global search capabilities of the algorithm. RPSO was the most effective variation in dealing with noise, closely followed by CRPSO. The latter variation is recommended for inverse heat conduction problems, as it combines the efficiency and effectiveness required by these problems.

Keywords: Inverse Analysis, Function Specification, Neural Net Works, Particle Swarm, Run Out Table.

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3693 Function Approximation with Radial Basis Function Neural Networks via FIR Filter

Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

Abstract:

Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore , the number of centers will be considered since it affects the performance of approximation.

Keywords: Extended kalmin filter (EKF), classification problem, radial basis function networks (RBFN), finite impulse response (FIR)filter.

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3692 Cryogenic Freezing Process Optimization Based On Desirability Function on the Path of Steepest Ascent

Authors: R. Uporn, P. Luangpaiboon

Abstract:

This paper presents a comparative study of statistical methods for the multi-response surface optimization of a cryogenic freezing process. Taguchi design and analysis and steepest ascent methods based on the desirability function were conducted to ascertain the influential factors of a cryogenic freezing process and their optimal levels. The more preferable levels of the set point, exhaust fan speed, retention time and flow direction are set at -90oC, 20 Hz, 18 minutes and Counter Current, respectively. The overall desirability level is 0.7044.

Keywords: Cryogenic Freezing Process, Taguchi Design and Analysis, Response Surface Method, Steepest Ascent Method and Desirability Function Approach.

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3691 Stability Analysis of Single Inverter Fed Two Induction Motors in Parallel

Authors: R. Gunabalan, V. Subbiah

Abstract:

This paper discusses the novel graphical approach for stability analysis of multi induction motor drive controlled by a single inverter. Stability issue arises in parallel connected induction motors under unbalanced load conditions. The two powerful globally accepted modeling and simulation software packages such as MATLAB and LabVIEW are selected to perform the stability analysis. The stability investigation is performed for different load conditions and difference in stator and rotor resistances among the two motors. It is very simple and effective than the techniques presented to obtain the stability of the parallel connected induction motor drive under unbalanced load conditions. Approximate transfer functions are considered to model the induction motors, load dynamics, speed controllers and inverter. Simulink library tools are utilized to model the entire drive scheme in MATLAB. Stability study is discussed in LabVIEW using control design and simulation toolkits. Simulation results are illustrated for various running conditions to demonstrate the effectiveness of the transfer function method.

Keywords: Induction motor, Modeling, Stability analysis, Transfer function model.

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3690 Certain Conditions for Strongly Starlike and Strongly Convex Functions

Authors: Sukhwinder Singh Billing, Sushma Gupta, Sukhjit Singh Dhaliwal

Abstract:

In the present paper, we investigate a differential subordination involving multiplier transformation related to a sector in the open unit disk E = {z : |z| < 1}. As special cases to our main result, certain sufficient conditions for strongly starlike and strongly convex functions are obtained.

Keywords: Analytic function, Multiplier transformation, Strongly starlike function, Strongly convex function.

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3689 Software Effort Estimation Models Using Radial Basis Function Network

Authors: E. Praynlin, P. Latha

Abstract:

Software Effort Estimation is the process of estimating the effort required to develop software. By estimating the effort, the cost and schedule required to estimate the software can be determined. Accurate Estimate helps the developer to allocate the resource accordingly in order to avoid cost overrun and schedule overrun. Several methods are available in order to estimate the effort among which soft computing based method plays a prominent role. Software cost estimation deals with lot of uncertainty among all soft computing methods neural network is good in handling uncertainty. In this paper Radial Basis Function Network is compared with the back propagation network and the results are validated using six data sets and it is found that RBFN is best suitable to estimate the effort. The Results are validated using two tests the error test and the statistical test.

Keywords: Software cost estimation, Radial Basis Function Network (RBFN), Back propagation function network, Mean Magnitude of Relative Error (MMRE).

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3688 Comparative Analysis of Sigmoidal Feedforward Artificial Neural Networks and Radial Basis Function Networks Approach for Localization in Wireless Sensor Networks

Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy

Abstract:

With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m2 grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.

Keywords: Localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI.

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3687 Classification of Initial Stripe Height Patterns using Radial Basis Function Neural Network for Proportional Gain Prediction

Authors: Prasit Wonglersak, Prakarnkiat Youngkong, Ittipon Cheowanish

Abstract:

This paper aims to improve a fine lapping process of hard disk drive (HDD) lapping machines by removing materials from each slider together with controlling the strip height (SH) variation to minimum value. The standard deviation is the key parameter to evaluate the strip height variation, hence it is minimized. In this paper, a design of experiment (DOE) with factorial analysis by twoway analysis of variance (ANOVA) is adopted to obtain a statistically information. The statistics results reveal that initial stripe height patterns affect the final SH variation. Therefore, initial SH classification using a radial basis function neural network is implemented to achieve the proportional gain prediction.

Keywords: Stripe height variation, Two-way analysis ofvariance (ANOVA), Radial basis function neural network, Proportional gain prediction.

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3686 The Global Stability Using Lyapunov Function

Authors: R. Kongnuy, E. Naowanich, T. Kruehong

Abstract:

An important technique in stability theory for differential equations is known as the direct method of Lyapunov. In this work we deal global stability properties of Leptospirosis transmission model by age group in Thailand. First we consider the data from Division of Epidemiology Ministry of Public Health, Thailand between 1997-2011. Then we construct the mathematical model for leptospirosis transmission by eight age groups. The Lyapunov functions are used for our model which takes the forms of an Ordinary Differential Equation system. The globally asymptotically for equilibrium states are analyzed.

Keywords: Age Group, Leptospirosis, Lyapunov Function, Ordinary Differential Equation.

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3685 Analysis on Fractals in Intuitionistic Fuzzy Metric Spaces

Authors: R. Uthayakumar, D. Easwaramoorthy

Abstract:

This paper investigates the fractals generated by the dynamical system of intuitionistic fuzzy contractions in the intuitionistic fuzzy metric spaces by generalizing the Hutchinson-Barnsley theory. We prove some existence and uniqueness theorems of fractals in the standard intuitionistic fuzzy metric spaces by using the intuitionistic fuzzy Banach contraction theorem. In addition to that, we analyze some results on intuitionistic fuzzy fractals in the standard intuitionistic fuzzy metric spaces with respect to the Hausdorff intuitionistic fuzzy metrics.

Keywords: Fractal Analysis, Fixed Point, Contraction, Iterated Function System, Intuitionistic Fuzzy Metric Space.

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3684 Alternative Convergence Analysis for a Kind of Singularly Perturbed Boundary Value Problems

Authors: Jiming Yang

Abstract:

A kind of singularly perturbed boundary value problems is under consideration. In order to obtain its approximation, simple upwind difference discretization is applied. We use a moving mesh iterative algorithm based on equi-distributing of the arc-length function of the current computed piecewise linear solution. First, a maximum norm a posteriori error estimate on an arbitrary mesh is derived using a different method from the one carried out by Chen [Advances in Computational Mathematics, 24(1-4) (2006), 197-212.]. Then, basing on the properties of discrete Green-s function and the presented posteriori error estimate, we theoretically prove that the discrete solutions computed by the algorithm are first-order uniformly convergent with respect to the perturbation parameter ε.

Keywords: Convergence analysis, green's function, singularly perturbed, equi-distribution, moving mesh.

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3683 Analysis of Blind Decision Feedback Equalizer Convergence: Interest of a Soft Decision

Authors: S. Cherif, S. Marcos, M. Jaidane

Abstract:

In this paper the behavior of the decision feedback equalizers (DFEs) adapted by the decision-directed or the constant modulus blind algorithms is presented. An analysis of the error surface of the corresponding criterion cost functions is first developed. With the intention of avoiding the ill-convergence of the algorithm, the paper proposes to modify the shape of the cost function error surface by using a soft decision instead of the hard one. This was shown to reduce the influence of false decisions and to smooth the undesirable minima. Modified algorithms using the soft decision during a pseudo-training phase with an automatic switch to the properly tracking phase are then derived. Computer simulations show that these modified algorithms present better ability to avoid local minima than conventional ones.

Keywords: Blind DFEs, decision-directed algorithm, constant modulus algorithm, cost function analysis, convergence analysis, soft decision.

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3682 A Case Study to Assess the Validity of Function Points

Authors: Neelam Bawane nee' Singhal, C. V. Srikrishna

Abstract:

Many metrics were proposed to evaluate the characteristics of the analysis and design model of a given product which in turn help to assess the quality of the product. Function point metric is a measure of the 'functionality' delivery by the software. This paper presents an analysis of a set of programs of a project developed in Cµ through Function Points metric. Function points are measured for a Data Flow Diagram (DFD) of the case developed at initial stage. Lines of Codes (LOCs) and possible errors are calculated with the help of measured Function Points (FPs). The calculations are performed using suitable established functions. Calculated LOCs and errors are compared with actual LOCs and errors found at the time of analysis & design review, implementation and testing. It has been observed that actual found errors are more than calculated errors. On the basis of analysis and observations, authors conclude that function point provides useful insight and helps to analyze the drawbacks in the development process.

Keywords: Function Points, Data Flow Diagram, Lines ofCodes.

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3681 Application the Statistical Conditional Entropy Function for Definition of Cause-and-Effect Relations during Primary Soil Formation

Authors: Vladimir K. Mukhomorov

Abstract:

Within the framework of a method of the information theory it is offered statistics and probabilistic model for definition of cause-and-effect relations in the coupled multicomponent subsystems. The quantitative parameter which is defined through conditional and unconditional entropy functions is introduced. The method is applied to the analysis of the experimental data on dynamics of change of the chemical elements composition of plants organs (roots, reproductive organs, leafs and stems). Experiment is directed on studying of temporal processes of primary soil formation and their connection with redistribution dynamics of chemical elements in plant organs. This statistics and probabilistic model allows also quantitatively and unambiguously to specify the directions of the information streams on plant organs.

Keywords: Chemical elements, entropy function, information, plants.

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3680 Calculation of Wave Function at the Origin (WFO) for the Ground State of Doubly Heavy Mesons Based On the Variational Method

Authors: Maryam Momeni Feili, Mahvash Zandy Navgaran

Abstract:

The wave function at the origin is an important quantity in studying many physical problems concerning heavy quarkonia. This is because that it is using for calculating spin state hyperfine splitting and also crucial to evaluating the production and decay amplitude of the heavy quarkonium. In this paper, we present the variational method by using the single-parameter wave function to estimate the WFO for the ground state of heavy mesons.

Keywords: Wave function at the origin, heavy mesons, bound states, variational method, non-relativistic quark model, potential model, trial wave function.

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3679 Recovering the Clipped OFDM Figurebased on the Conic Function

Authors: Linjun Wu, Shihua Zhu, Xingle Feng

Abstract:

In Orthogonal Frequency Division Multiplexing (OFDM) systems, the peak to average power ratio (PAR) is much high. The clipping signal scheme is a useful method to reduce PAR. Clipping the OFDM signal, however, increases the overall noise level by introducing clipping noise. It is necessary to recover the figure of the original signal at receiver in order to reduce the clipping noise. Considering the continuity of the signal and the figure of the peak, we obtain a certain conic function curve to replace the clipped signal module within the clipping time. The results of simulation show that the proposed scheme can reduce the systems? BER (bit-error rate) 10 times when signal-to-interference-and noise-ratio (SINR) equals to 12dB. And the BER performance of the proposed scheme is superior to that of kim's scheme, too.

Keywords: Orthogonal Frequency Division Multiplexing, Peak-to-Average Power Ratio, clipping time, conic function.

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3678 Statistical Approach to Basis Function Truncation in Digital Interpolation Filters

Authors: F. Castillo, J. Arellano, S. Sánchez

Abstract:

In this paper an alternative analysis in the time domain is described and the results of the interpolation process are presented by means of functions that are based on the rule of conditional mathematical expectation and the covariance function. A comparison between the interpolation error caused by low order filters and the classic sinc(t) truncated function is also presented. When fewer samples are used, low-order filters have less error. If the number of samples increases, the sinc(t) type functions are a better alternative. Generally speaking there is an optimal filter for each input signal which depends on the filter length and covariance function of the signal. A novel scheme of work for adaptive interpolation filters is also presented.

Keywords: Interpolation, basis function, over-sampling.

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3677 A Transfer Function Representation of Thermo-Acoustic Dynamics for Combustors

Authors: Myunggon Yoon, Jung-Ho Moon

Abstract:

In this paper, we present a transfer function representation of a general one-dimensional combustor. The input of the transfer function is a heat rate perturbation of a burner and the output is a flow velocity perturbation at the burner. This paper considers a general combustor model composed of multiple cans with different cross sectional areas, along with a non-zero flow rate.

Keywords: Thermoacoustics, dynamics, combustor, transfer function.

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3676 Studying Mistaken Theory of Calendar Function of Iran-s Cross-Vaults

Authors: Ali Salehipour

Abstract:

After presenting the theory of calendar function of Iran-s cross-vaults especially “Niasar" cross-vault in recent years, there has been lots of doubts and uncertainty about this theory by astrologists and archaeologists. According to this theory “Niasar cross-vault and other cross-vaults of Iran has calendar function and are constructed in a way that sunrise and sunset can be seen from one of its openings in the beginning and middle of each season of year". But, mentioning historical documentaries we conclude here that the theory of calendar function of Iran-s cross-vaults does not have any strong basis and individual cross-vaults had only religious function in Iran.

Keywords: cross-vault, fire temple, Calendar function, Sassanid period

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3675 Training Radial Basis Function Networks with Differential Evolution

Authors: Bing Yu , Xingshi He

Abstract:

In this paper, Differential Evolution (DE) algorithm, a new promising evolutionary algorithm, is proposed to train Radial Basis Function (RBF) network related to automatic configuration of network architecture. Classification tasks on data sets: Iris, Wine, New-thyroid, and Glass are conducted to measure the performance of neural networks. Compared with a standard RBF training algorithm in Matlab neural network toolbox, DE achieves more rational architecture for RBF networks. The resulting networks hence obtain strong generalization abilities.

Keywords: differential evolution, neural network, Rbf function

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3674 Measuring Teachers- Beliefs about Mathematics: A Fuzzy Set Approach

Authors: M.A. Lazim, M.T.Abu Osman

Abstract:

This paper deals with the application of a fuzzy set in measuring teachers- beliefs about mathematics. The vagueness of beliefs was transformed into standard mathematical values using a fuzzy preferences model. The study employed a fuzzy approach questionnaire which consists of six attributes for measuring mathematics teachers- beliefs about mathematics. The fuzzy conjoint analysis approach based on fuzzy set theory was used to analyze the data from twenty three mathematics teachers from four secondary schools in Terengganu, Malaysia. Teachers- beliefs were recorded in form of degrees of similarity and its levels of agreement. The attribute 'Drills and practice is one of the best ways of learning mathematics' scored the highest degree of similarity at 0. 79860 with level of 'strongly agree'. The results showed that the teachers- beliefs about mathematics were varied. This is shown by different levels of agreement and degrees of similarity of the measured attributes.

Keywords: belief, membership function, degree of similarity, conjoint analysis

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3673 Estimation of Production Function in Fishery on the Coasts of Caspian Sea

Authors: Komeil Jahanifar, Zahra Abedi, Yaghob Zeraatkish

Abstract:

This research was conducted for the first time at the southeastern coasts of the Caspian Sea in order to evaluate the performance of osteichthyes cooperatives through production (catch) function. Using one of the indirect valuation methods in this research, contributory factors in catch were identified and were inserted into the function as independent variables. In order to carry out this research, the performance of 25 Osteichthyes catching cooperatives in the utilization year of 2009 which were involved in fishing in Miankale wildlife refuge region. The contributory factors in catch were divided into groups of economic, ecological and biological factors. In the mentioned function, catch rate of the cooperative were inserted into as the dependant variable and fourteen partial variables in terms of nine general variables as independent variables. Finally, after function estimation, seven variables were rendered significant at 99 percent reliably level. The results of the function estimation indicated that human resource (fisherman quantity) had the greatest positive effect on catch rate with an influence coefficient of 1.7 while weather conditions had the greatest negative effect on the catch rate of cooperatives with an influence coefficient of -2.07. Moreover, factors like member's share, experience and fisherman training and fishing effort played the main roles in the catch rate of cooperative with influence coefficients of 0.81, 0.5 and 0.21, respectively.

Keywords: Production Function, Coefficient, Variable, Osteichthyes, Caspian Sea

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