Search results for: Exponential autoregressive model

Authors: Georgi Yordanov Georgiev, Michael Daly, Erin Gombos, Amrit Vinod, Gajinder Hoonjan

Abstract:

Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system - the central processing unit (CPU) of computers. The quantity of organization for several generations of CPUs shows a double exponential rate of change of organization with time. The exact functional dependence has a fine, S-shaped structure, revealing some of the mechanisms of self-organization. The principle of least action helps to explain the mechanism of increase of organization through quantity accumulation and constraint and curvature minimization with an attractor, the least average sum of actions of all elements and for all motions. This approach can help describe, quantify, measure, manage, design and predict future behavior of complex systems to achieve the highest rates of self organization to improve their quality. It can be applied to other complex systems from Physics, Chemistry, Biology, Ecology, Economics, Cities, network theory and others where complex systems are present.

Keywords: Organization, self-organization, complex system, complexification, quantitative measure, principle of least action, principle of stationary action, attractor, progressive development, acceleration, stochastic.

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the egovernment portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an egovernment maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: Best practices, e-government portal, maturity model, quality model.

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Authors: Joanna Sooknanan, Donna Comissiong

Abstract:

We propose a phenomenological model for the process of polymer desorption. In so doing, we omit the usual theoretical approach of incorporating a fictitious viscoelastic stress term into the flux equation. As a result, we obtain a model that captures the essence of the phenomenon of trapping skinning, while preserving the integrity of the experimentally verified Fickian law for diffusion. An appropriate asymptotic analysis is carried out, and a parameter is introduced to represent the speed of the desorption front. Numerical simulations are performed to illustrate the desorption dynamics of the model. Recommendations are made for future modifications of the model, and provisions are made for the inclusion of experimentally determined frontal speeds.

Keywords: Phenomenological Model, Polymer, Desorption, Trapping Skinning

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Authors: Y. A. Shapovalov, F. M. Gumerov, M. K. Nauryzbaev, S. V. Mazanov, R. A. Usmanov, A. V. Klinov, L. K. Safiullina, S. A. Soshin

Abstract:

A flow-through installation was created and manufactured for the transesterification of triglycerides of fatty acids and production of biodiesel fuel under supercritical fluid conditions. Transesterification of rapeseed oil with ethanol was carried out according to two parameters: temperature and the ratio of alcohol/oil mixture at the constant pressure of 19 MPa. The kinetics of the yield of fatty acids ethyl esters (FAEE) was determined in the temperature range of 320-380 °C at the alcohol/oil molar ratio of 6:1-20:1. The content of the formed FAEE was determined by the method of correlation of the resulting biodiesel fuel by its kinematic viscosity. The maximum FAEE yield (about 90%) was obtained within 30 min at the ethanol/oil molar ratio of 12:1 and a temperature of 380 °C. When studying of transesterification of triglycerides, a kinetic model of an isothermal flow reactor was used. The reaction order implemented in the flow reactor has been determined. The first order of the reaction was confirmed by data on the conversion of FAEE during the reaction at different temperatures and the molar ratios of the initial reagents (ethanol/oil). Using the Arrhenius equation, the values of the effective constants of the transesterification reaction rate were calculated at different reaction temperatures. In addition, based on the experimental data, the activation energy and the pre-exponential factor of the transesterification reaction were determined.

Keywords: Biodiesel, fatty acid esters, supercritical fluid technology, transesterification.

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Authors: Rui. Zhang, Yiming. Pi

Abstract:

In this paper we present a novel approach for human Body configuration based on the Silhouette. We propose to address this problem under the Bayesian framework. We use an effective Model based MCMC (Markov Chain Monte Carlo) method to solve the configuration problem, in which the best configuration could be defined as MAP (maximize a posteriori probability) in Bayesian model. This model based MCMC utilizes the human body model to drive the MCMC sampling from the solution space. It converses the original high dimension space into a restricted sub-space constructed by the human model and uses a hybrid sampling algorithm. We choose an explicit human model and carefully select the likelihood functions to represent the best configuration solution. The experiments show that this method could get an accurate configuration and timesaving for different human from multi-views.

Keywords: Bayesian framework, MCMC, model based, human body configuration.

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Authors: Noor A. Auzairy, Rubi Ahmad, Catherine S.F. Ho, Ros Z. Z. Sapian

Abstract:

This paper is to explore the relationship and the level of stock market integration of the Asian countries, primarily concentrating on Malaysia, Thailand, Indonesia, and South Korea, with the world from January 1997 to December 2009. The degree of short-run and long-run stock market integration of those Asian countries are analyzed in order to determine the significance of series of regional and world financial crises, liberalization policies and other financial reforms in influencing the level of stock market integration. To test for cointegration, this paper applies coefficient correlation, univariate regression analyses, cointegration tests, and vector autoregressive models (VAR) by using the four Asian stock markets main indices and the MSCI World index. The empirical findings from this work reveal that there is no long-run stock market integration for the four countries and the world market. However, there is short run integration.

Keywords: Asia, integration, relationship, stock market.

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Authors: S.Ali Al-Mawsawi

Abstract:

In this paper, a new developed construction model of the UPFC is proposed. The construction of this model consists of one shunt compensation block and two series compensation blocks. In this case, the UPFC with the new construction model will be investigated when it is installed in multi-machine systems with nonlinear load model. In addition, the steady–state performance of the new model operating as impedance compensation will be presented and compared with that obtained from the system without compensation.

Keywords: UPFC, PWM, Nonlinear load, Multi-Machines system

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Authors: Hamed Rafiei, Masoud Rabbani

Abstract:

This paper addresses one of the most important issues have been considered in hybrid MTS/MTO production environments. To cope with the problem, a mathematical programming model is applied from a tactical point of view. The model is converted to a fuzzy goal programming model, because a degree of uncertainty is involved in hybrid MTS/MTO context. Finally, application of the proposed model in an industrial center is reported and the results prove the validity of the model.

Keywords: Fuzzy sets theory, Hybrid MTS/MTO, Order penetration point, Quadratic programming.

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Authors: Krzysztof Fujarewicz

Abstract:

This paper presents a predictive model of sensor readings for mobile robot. The model predicts sensor readings for given time horizon based on current sensor readings and velocities of wheels assumed for this horizon. Similar models for such anticipation have been proposed in the literature. The novelty of the model presented in the paper comes from the fact that its structure takes into account physical phenomena and is not just a black box, for example a neural network. From this point of view it may be regarded as a semi-phenomenological model. The model is developed for the Khepera robot, but after certain modifications, it may be applied for any robot with distance sensors such as infrared or ultrasonic sensors.

Keywords: Mobile robot, sensors, prediction, anticipation.

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Authors: Barath Kumar, Oliver Niggemann, Juergen Jasperneite

Abstract:

Model-based approaches have been applied successfully to a wide range of tasks such as specification, simulation, testing, and diagnosis. But one bottleneck often prevents the introduction of these ideas: Manual modeling is a non-trivial, time-consuming task. Automatically deriving models by observing and analyzing running systems is one possible way to amend this bottleneck. To derive a model automatically, some a-priori knowledge about the model structure–i.e. about the system–must exist. Such a model formalism would be used as follows: (i) By observing the network traffic, a model of the long-term system behavior could be generated automatically, (ii) Test vectors can be generated from the model, (iii) While the system is running, the model could be used to diagnose non-normal system behavior. The main contribution of this paper is the introduction of a model formalism called 'probabilistic regression automaton' suitable for the tasks mentioned above.

Keywords: Model-based approach, Probabilistic regression automata, Statistical models and Timed automata.

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Authors: Javad Marzbanrad, Mostafa Pahlavani

Abstract:

This study has investigated a vehicle Lumped Parameter Model (LPM) in frontal crash. There are several ways for determining spring and damper characteristics and type of problem shall be considered as system identification. This study use Genetic Algorithm (GA) procedure, being an effective procedure in case of optimization issues, for optimizing errors, between target data (experimental data) and calculated results (being obtained by analytical solving). In this study analyzed model in 5-DOF then compared our results with 5-DOF serial model. Finally, the response of model due to external excitement is investigated.

Keywords: Vehicle, Lumped-Parameter Model, GeneticAlgorithm, Optimization

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Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

Abstract:

After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR.

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Authors: Jolanta Tamošaitienė

Abstract:

The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: Assessment, environment, agile, model, risk.

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Authors: Mohammad Mohammad

Abstract:

With the exponential progress of technological development comes a strong sense that events are moving too quickly for our schools and that teachers may be losing control of them in the process. This paper examines the impact of e-learning and e-teaching in universities, from both the student and teacher perspective. In particular, it is shown that e-teachers should focus not only on the technical capacities and functions of IT materials and activities, but must attempt to more fully understand how their e-learners perceive the learning environment. From the e-learner perspective, this paper indicates that simply having IT tools available does not automatically translate into all students becoming effective learners. More evidence-based evaluative research is needed to allow e-learning and e-teaching to reach full potential.

Keywords: e-learning, e-teaching, distance learning, education

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Authors: Tamara Nestorović, Jean Lefèvre, Stefan Ringwelski, Ulrich Gabbert

Abstract:

Two approaches for model development of a smart acoustic box are suggested in this paper: the finite element (FE) approach and the subspace identification. Both approaches result in a state-space model, which can be used for obtaining the frequency responses and for the controller design. In order to validate the developed FE model and to perform the subspace identification, an experimental set-up with the acoustic box and dSPACE system was used. Experimentally obtained frequency responses show good agreement with the frequency responses obtained from the FE model and from the identified model.

Keywords: Acoustic box, experimental verification, finite element model, subspace identification.

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Authors: Wararat Rungworawut, Twittie Senivongse

Abstract:

Business process model describes process flow of a business and can be seen as the requirement for developing a software application. This paper discusses a BPM2CD guideline which complements the Model Driven Architecture concept by suggesting how to create a platform-independent software model in the form of a UML class diagram from a business process model. An important step is the identification of UML classes from the business process model. A technique for object-oriented analysis called domain analysis is borrowed and key concepts in the business process model will be discovered and proposed as candidate classes for the class diagram. The paper enhances this step by using ontology search to help identify important classes for the business domain. As ontology is a source of knowledge for a particular domain which itself can link to ontologies of related domains, the search can give a refined set of candidate classes for the resulting class diagram.

Keywords: Business Process Model, Model DrivenArchitecture, Ontology, UML Class Diagram.

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Authors: Yongsuk Jang Kim, Sun-Tae Chung, Boogyun Kim, Seongwon Cho

Abstract:

Realistic 3D face model is more precise in representing pose, illumination, and expression of face than 2D face model so that it can be utilized usefully in various applications such as face recognition, games, avatars, animations, and etc. In this paper, we propose a 3D face modeling method based on 3D dense morphable shape model. The proposed 3D modeling method first constructs a 3D dense morphable shape model from 3D face scan data obtained using a 3D scanner. Next, the proposed method extracts and matches facial landmarks from 2D image sequence containing a face to be modeled, and then reconstructs 3D vertices coordinates of the landmarks using a factorization-based SfM technique. Then, the proposed method obtains a 3D dense shape model of the face to be modeled by fitting the constructed 3D dense morphable shape model into the reconstructed 3D vertices. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method generates a 3D face model by rendering the 3D dense face shape model using the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise.

Keywords: 3D Face Modeling, 3D Morphable Shape Model, 3DReconstruction, 3D Correspondence.

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Authors: Ahmad F. Subahi, Anthony J. H. Simons

Abstract:

This Paper presents an on-going research in the area of Model-Driven Engineering (MDE). The premise is that UML is too unwieldy to serve as the basis for model-driven engineering. We need a smaller, simpler notation with a cleaner semantics. We propose some ideas for a simpler notation with a clean semantics. The result is known as μML, or the Micro-Modelling Language.

Keywords: Model-driven engineering, model transformations, domain-specific languages, end-user development.

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Authors: Zixin Liu, Huawei Yang, Fangwei Chen

Abstract:

In this paper, the issue of pth moment stability of a class of stochastic neural networks with mixed delays is investigated. By establishing two integro-differential inequalities, some new sufficient conditions ensuring pth moment exponential stability are obtained. Compared with some previous publications, our results generalize some earlier works reported in the literature, and remove some strict constraints of time delays and kernel functions. Two numerical examples are presented to illustrate the validity of the main results.

Keywords: Neural networks, stochastic, PTH moment stable, time varying delays, distributed delays.

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Authors: Catherine Maware, Olufemi Adetunji

Abstract:

The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: Impact measurement model, lean bundles, lean manufacturing, organizational performance.

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Authors: Natalia Koltovaya, Nadezhda Zhuchkina, Ksenia Lyubimova

Abstract:

We study the biological effects induced by ionizing radiation in view of therapeutic exposure and the idea of space flights beyond Earth's magnetosphere. In particular, we examine the differences between base pair substitution induction by ionizing radiation in model haploid and diploid yeast Saccharomyces cerevisiae cells. Such mutations are difficult to study in higher eukaryotic systems. In our research, we have used a collection of six isogenic trp5-strains and 14 isogenic haploid and diploid cyc1-strains that are specific markers of all possible base-pair substitutions. These strains differ from each other only in single base substitutions within codon-50 of the trp5 gene or codon-22 of the cyc1 gene. Different mutation spectra for two different haploid genetic trp5- and cyc1-assays and different mutation spectra for the same genetic cyc1-system in cells with different ploidy — haploid and diploid — have been obtained. It was linear function for dose-dependence in haploid and exponential in diploid cells. We suggest that the differences between haploid yeast strains reflect the dependence on the sequence context, while the differences between haploid and diploid strains reflect the different molecular mechanisms of mutations.

Keywords: Base pair substitutions, γ-rays, haploid and diploid cells, yeast Saccharomyces cerevisiae.

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Authors: Y. Boutiche, N. Ramou, M. Ben Gharsallah

Abstract:

This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.

Keywords: Active contour, Chan-Vese Model, local segmentation, weld radiographic images.

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Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

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Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

Abstract:

Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: Cache system, formal verification, novel model, System on Chip (SoC).

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Authors: Widad Jakjoud, Mohamed Bahaj, Jamal Bakkas

Abstract:

Through this paper we present a method for automatic generation of ontological model from any data source using Model Driven Architecture (MDA), this generation is dedicated to the cooperation of the knowledge engineering and software engineering. Indeed, reverse engineering of a data source generates a software model (schema of data) that will undergo transformations to generate the ontological model. This method uses the meta-models to validate software and ontological models.

Keywords: Meta model, model, ontology, data source.

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Authors: Y. N. Phang, E. F. Loh

Abstract:

Zero inflated strict arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, we extend zero inflated strict arcsine model to zero inflated strict arcsine regression model by taking into consideration the extra variability caused by extra zeros and covariates in count data. Maximum likelihood estimation method is used in estimating the parameters for this zero inflated strict arcsine regression model.

Keywords: Overdispersed count data, maximum likelihood estimation, simulated annealing.

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Authors: Miljan B. Petrović, Dušan B. Petrović, Goran S. Nikolić

Abstract:

This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful.

Keywords: Noise, signal-to-noise ratio, stochastic signals, variance estimation.

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Authors: Maqbool Hussain Sial, Maaida Hussain Hashmi, Sofia Anwar

Abstract:

The present research was focused to investigate the role of investment in the course of economic growth with reference to Pakistan. The study analyzed the role of the public and private investment and impact of the political and macroeconomic uncertainty on economic growth of Pakistan by using the vector autoregressive approach (VAR). In long-run both public and private investment showed a positive impact on economic growth but the growth was largely driven by private investment as compared to public investment. Government consumption expenditure, economic uncertainty and political instability hampered the economic growth of Pakistan. In short-run the private investment positively influences the growth but there was negative and insignificant effect of the public investment and government consumption expenditure on the growth. There was a positive relationship found between economic uncertainty (proxy for inflation) and GDP in short run.

Keywords: Investment, Government Consumption, Growth, Co-integration, Pakistan.

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Authors: Hidehiko Okada

Abstract:

The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks. 

Keywords: Evolutionary algorithms, differential evolution, neural network, neuroevolution, interval arithmetic.

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Authors: M. W. Siddiqi, M. Ilyas

Abstract:

Availability and mobilization of revenue is the main essential with which an economy is managed and run. While planning or while making the budgets nations set revenue targets to be achieved. But later when the accounts are closed the actual collections of revenue through taxes or even the non-tax revenue collection would invariably be different as compared to the initial estimates and targets set to be achieved. This revenue-gap distorts the whole system and the economy disturbing all the major macroeconomic indicators. This study is aimed to find out short and long term impact of revenue gap on budget deficit, debt burden and economic growth on the economy of Pakistan. For this purpose the study uses autoregressive distributed lag approach to cointegration and error correction mechanism on three different models for the period 1980 to 2009. The empirical results show that revenue gap has a short and long run relationship with economic growth and budget deficit. However, revenue gap has no impact on debt burden.

Keywords: Revenue Gap, Economic Growth, Budget Deficit, Debt Burden

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