Search results for: heuristic rules

Authors: Gints Jekabsons

Abstract:

The approach of subset selection in polynomial regression model building assumes that the chosen fixed full set of predefined basis functions contains a subset that is sufficient to describe the target relation sufficiently well. However, in most cases the necessary set of basis functions is not known and needs to be guessed – a potentially non-trivial (and long) trial and error process. In our research we consider a potentially more efficient approach – Adaptive Basis Function Construction (ABFC). It lets the model building method itself construct the basis functions necessary for creating a model of arbitrary complexity with adequate predictive performance. However, there are two issues that to some extent plague the methods of both the subset selection and the ABFC, especially when working with relatively small data samples: the selection bias and the selection instability. We try to correct these issues by model post-evaluation using Cross-Validation and model ensembling. To evaluate the proposed method, we empirically compare it to ABFC methods without ensembling, to a widely used method of subset selection, as well as to some other well-known regression modeling methods, using publicly available data sets.

Keywords: Basis function construction, heuristic search, modelensembles, polynomial regression.

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Authors: Ikbal Zammouri, Béchir Ayeb

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In this paper, we propose a new method to describe fractal shapes using parametric l-systems. First we introduce scaling factors in the production rules of the parametric l-systems grammars. Then we decorticate these grammars with scaling factors using turtle algebra to show the mathematical relation between l-systems and iterated function systems (IFS). We demonstrate that with specific values of the scaling factors, we find the exact relationship established by Prusinkiewicz and Hammel between l-systems and IFS.

Keywords: Fractal shapes, IFS, parametric l-systems, turtlealgebra.

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Authors: Mian Tahir Aftab, Muhammad Umer, Riaz Ahmad

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This article proposes an Ant Colony Optimization (ACO) metaheuristic to minimize total makespan for scheduling a set of jobs and assign workers for uniformly related parallel machines. An algorithm based on ACO has been developed and coded on a computer program Matlab®, to solve this problem. The paper explains various steps to apply Ant Colony approach to the problem of minimizing makespan for the worker assignment & jobs scheduling problem in a parallel machine model and is aimed at evaluating the strength of ACO as compared to other conventional approaches. One data set containing 100 problems (12 Jobs, 03 machines and 10 workers) which is available on internet, has been taken and solved through this ACO algorithm. The results of our ACO based algorithm has shown drastically improved results, especially, in terms of negligible computational effort of CPU, to reach the optimal solution. In our case, the time taken to solve all 100 problems is even lesser than the average time taken to solve one problem in the data set by other conventional approaches like GA algorithm and SPT-A/LMC heuristics.

Keywords: Ant Colony Optimization (ACO), Genetic algorithms (GA), Makespan, SPT-A/LMC heuristic.

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Authors: Marisa Catarina da Conceição Dinis

Abstract:

The commercial companies’ management has suffered an important material and legal transformation in the last years, mainly related to the changes in the Portuguese legal framework and because of the fact they were recently object of great expansion. In fact, next to the smaller family businesses, whose management is regularly assumed by partners, companies with social investment highly scattered, whose owners are completely out from administration, are now arising. In those particular cases, the business transactions are much more complex and require from the companies’ managers a highly technical knowledge and some specific professionals’ skills and abilities. This kind of administration carries a high-level risk that can both result in great success or in great losses. Knowing that the administration performance can result in important losses to the companies, the Portuguese legislator has created a legal structure to impute them some responsibilities and sanctions. The main goal of this study is to analyze the Portuguese law and some jurisprudence about companies’ management rules and about the conflicts between the directors and the company. In order to achieve these purposes we have to consider, on the one hand, the legal duties directly connected to the directors’ functions and on the other hand the disrespect for those same rules. The Portuguese law in this matter, influenced by the common law, determines that the directors’ attitude should be guided by loyalty and honesty. Consequently, we must reflect in which cases the administrators should respond to losses that they might cause to companies as a result of their duties’ disrespect. In this way is necessary to study the business judgment rule wich is a rule that refers to a liability exclusion rule. We intend, in the same way, to evaluate if the civil liability that results from the directors’ duties disrespect can extend itself to those who have elected them ignoring or even knowing that they don´t have the necessary skills or appropriate knowledge to the position they hold. To charge directors’, without ruining entrepreneurship, charging, in the same way, those who select them reinforces the need for more responsible and cautious attitudes which will lead consequently to more confidence in the markets.

Keywords: Duty of loyalty, duty of care, business judgment rule, civil liability of directors.

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Authors: Miloš Šeda, Tomáš Březina

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In this paper, we focus on the use of knowledge bases in two different application areas – control of systems with unknown or strongly nonlinear models (i.e. hardly controllable by the classical methods), and robot motion planning in eight directions. The first one deals with fuzzy logic and the paper presents approaches for setting and aggregating the rules of a knowledge base. Te second one is concentrated on a case-based reasoning strategy for finding the path in a planar scene with obstacles.

Keywords: fuzzy controller, fuzzification, rule base, inference, defuzzification, genetic algorithm, neural network, case-based reasoning

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Authors: Anurag Sharma, Christian W. Omlin

Abstract:

Self-organizing map (SOM) is a well known data reduction technique used in data mining. It can reveal structure in data sets through data visualization that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOM, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of an adaptive heuristic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOM. The application of our method to several standard data sets demonstrates its feasibility. PSO algorithm utilizes a so-called U-matrix of SOM to determine cluster boundaries; the results of this novel automatic method compare very favorably to boundary detection through traditional algorithms namely k-means and hierarchical based approach which are normally used to interpret the output of SOM.

Keywords: cluster boundaries, clustering, code vectors, data mining, particle swarm optimization, self-organizing maps, U-matrix.

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Authors: K. Varesi

Abstract:

This paper proposes a Particle Swarm Optimization (PSO) based technique for the optimal allocation of Distributed Generation (DG) units in the power systems. In this paper our aim is to decide optimal number, type, size and location of DG units for voltage profile improvement and power loss reduction in distribution network. Two types of DGs are considered and the distribution load flow is used to calculate exact loss. Load flow algorithm is combined appropriately with PSO till access to acceptable results of this operation. The suggested method is programmed under MATLAB software. Test results indicate that PSO method can obtain better results than the simple heuristic search method on the 30-bus and 33- bus radial distribution systems. It can obtain maximum loss reduction for each of two types of optimally placed multi-DGs. Moreover, voltage profile improvement is achieved.

Keywords: Distributed Generation (DG), Optimal Allocation, Particle Swarm Optimization (PSO), Power Loss Minimization, Voltage Profile Improvement.

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Authors: Pei-Chann Chang, Wei-Hsiu Huang, Ching-Jung Ting, Hwei-Wen Luo, Yu-Peng Yu

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Artificial Immune System is applied as a Heuristic Algorithm for decades. Nevertheless, many of these applications took advantage of the benefit of this algorithm but seldom proposed approaches for enhancing the efficiency. In this paper, a Self-evolving Artificial Immune System is proposed via developing the T and B cell in Immune System and built a self-evolving mechanism for the complexities of different problems. In this research, it focuses on enhancing the efficiency of Clonal selection which is responsible for producing Affinities to resist the invading of Antigens. T and B cell are the main mechanisms for Clonal Selection to produce different combinations of Antibodies. Therefore, the development of T and B cell will influence the efficiency of Clonal Selection for searching better solution. Furthermore, for better cooperation of the two cells, a co-evolutional strategy is applied to coordinate for more effective productions of Antibodies. This work finally adopts Flow-shop scheduling instances in OR-library to validate the proposed algorithm.

Keywords: Artificial Immune System, Clonal Selection, Flow-shop Scheduling Problems, Co-evolutional strategy

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Authors: Mohammad Reza Karami Nejad

Abstract:

A hybrid learning automata-genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP-Complete problem. In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed HLGA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. Simulation results demonstrate that this paper proposed algorithm not only has the fast calculating speed and high accuracy but also can improve the efficiency in Next Generation Networks QoS routing. The proposed algorithm has overcome all of the previous algorithms in the literature.

Keywords: Routing, Quality of Service, Multicaset, Learning Automata, Genetic, Next Generation Networks.

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Authors: Reza Moosavi Mohseni, Wenjun Zhang, Jiling Cao

Abstract:

The aim of the present study is to detect the chaotic behavior in monetary economic relevant dynamical system. The study employs three different forms of Taylor rules: current, forward, and backward looking. The result suggests the existence of the chaotic behavior in all three systems. In addition, the results strongly represent that using expectations in policy rule especially rational expectation hypothesis can increase complexity of the system and leads to more chaotic behavior.

Keywords: Chaos theory, GMM estimator, Lyapunov Exponent, Monetary System, Taylor Rule.

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Authors: M. A. Sharbafi, M. Shakiba Herfeh, Caro Lucas, A. Mohammadi Nejad

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Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of GA to obtain fuzzy rules and application of fuzzy logic in optimization of GA). In this paper, we suggest a new method in which fuzzy decision making is used to improve the performance of genetic algorithm. In the suggested method, we determine the alleles that enhance the fitness of chromosomes and try to insert them to the next generation. In this algorithm we try to present an innovative vaccination in the process of reproduction in genetic algorithm, with considering the trade off between exploration and exploitation.

Keywords: Genetic Algorithm, Fuzzy Decision Making.

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Authors: E. Al Daoud

Abstract:

In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.

Keywords: Feynman rules, hadrons, Lagrangian, Monte Carlo, simulation.

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Authors: Hee Suk Seo, Tae Kyung Kim

Abstract:

As network components grow larger and more diverse, and as securing them on a host-by-host basis grow more difficult, more sites are turning to a network security model. We concentrate on controlling network access to various hosts and the services they offer, rather than on securing them one by one with a network security model. We present how the policy rules from vulnerabilities stored in SVDB (Simulation based Vulnerability Data Base) are inducted, and how to be used in PBN. In the network security environment, each simulation model is hierarchically designed by DEVS (Discrete EVent system Specification) formalism.

Keywords: SVDB, PBN, DEVS, Network security.

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Authors: Oscar E. Ruiz, Carlos Cadavid, Juan G. Lalinde, Ricardo Serrano, Guillermo Peris-Fajarnes

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The Boundary Representation of a 3D manifold contains FACES (connected subsets of a parametric surface S : R2 -! R3). In many science and engineering applications it is cumbersome and algebraically difficult to deal with the polynomial set and constraints (LOOPs) representing the FACE. Because of this reason, a Piecewise Linear (PL) approximation of the FACE is needed, which is usually represented in terms of triangles (i.e. 2-simplices). Solving the problem of FACE triangulation requires producing quality triangles which are: (i) independent of the arguments of S, (ii) sensitive to the local curvatures, and (iii) compliant with the boundaries of the FACE and (iv) topologically compatible with the triangles of the neighboring FACEs. In the existing literature there are no guarantees for the point (iii). This article contributes to the topic of triangulations conforming to the boundaries of the FACE by applying the concept of parameterindependent Gabriel complex, which improves the correctness of the triangulation regarding aspects (iii) and (iv). In addition, the article applies the geometric concept of tangent ball to a surface at a point to address points (i) and (ii). Additional research is needed in algorithms that (i) take advantage of the concepts presented in the heuristic algorithm proposed and (ii) can be proved correct.

Keywords: surface triangulation, conforming triangulation, surfacesampling, Gabriel complex.

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Authors: M. Kargar, R. Mirmiran, F. Fartash, T. Saderi

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In this paper a new method is suggested for risk management by the numerical patterns in data-mining. These patterns are designed using probability rules in decision trees and are cared to be valid, novel, useful and understandable. Considering a set of functions, the system reaches to a good pattern or better objectives. The patterns are analyzed through the produced matrices and some results are pointed out. By using the suggested method the direction of the functionality route in the systems can be controlled and best planning for special objectives be done.

Keywords: Analysis, Data-mining, Pattern, Risk Management.

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Authors: Bachir Bentouati, Lakhdar Chaib, Saliha Chettih, Gai-Ge Wang

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The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

Keywords: Stud Krill Herd, economic dispatch, crossover, stud selection, valve-point effect.

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Authors: Swathi Sampath, V. Kalaichelvi

Abstract:

The assessment of the risk posed by a borrower to a lender is one of the common problems that financial institutions have to deal with. Consumers vying for a mortgage are generally compared to each other by the use of a number called the Credit Score, which is generated by applying a mathematical algorithm to information in the applicant’s credit report. The higher the credit score, the lower the risk posed by the candidate, and the better he is to be taken on by the lender. The objective of the present work is to use fuzzy logic and linguistic rules to create a model that generates Credit Scores.

Keywords: Credit scoring, fuzzy logic, mortgage, risk assessment.

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Authors: Anis Gharbi

Abstract:

This paper considers the problem of scheduling maintenance actions for identical aircraft gas turbine engines. Each one of the turbines consists of parts which frequently require replacement. A finite inventory of spare parts is available and all parts are ready for replacement at any time. The inventory consists of both new and refurbished parts. Hence, these parts have different field lives. The goal is to find a replacement part sequencing that maximizes the time that the aircraft will keep functioning before the inventory is replenished. The problem is formulated as an identical parallel machine scheduling problem where the minimum completion time has to be maximized. Two models have been developed. The first one is an optimization model which is based on a 0-1 linear programming formulation, while the second one is an approximate procedure which consists in decomposing the problem into several two-machine subproblems. Each subproblem is optimally solved using the first model. Both models have been implemented using Lingo and have been tested on two sets of randomly generated data with up to 150 parts and 10 turbines. Experimental results show that the optimization model is able to solve only instances with no more than 4 turbines, while the decomposition procedure often provides near-optimal solutions within a maximum CPU time of 3 seconds.

Keywords: Aircraft turbines, Scheduling, Identical parallel machines, 0-1 linear programming, Heuristic.

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Authors: Yun Bai

Abstract:

As a security mechanism, authorization is to provide access control to the system resources according to the polices and rules specified by the security strategies. Either by update or in the initial specification, conflicts in authorization is an issue needs to be solved. In this paper, we propose a new approach to solve conflict by using prioritized logic programs and discuss the uniqueness of its answer set. Addressing conflict resolution from logic programming viewpoint and the uniqueness analysis of the answer set provide a novel, efficient approach for authorization conflict resolution.

Keywords: authorization, formal specification, conflict resolution, prioritized logic program.

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Authors: Ru-Shuo Sheu, Han-Hsin Chou, Te-Shyang Tan

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Considering a reservoir with periodic states and different cost functions with penalty, its release rules can be modeled as a periodic Markov decision process (PMDP). First, we prove that policy- iteration algorithm also works for the PMDP. Then, with policy- iteration algorithm, we obtain the optimal policies for a special aperiodic reservoir model with two cost functions under large penalty and give a discussion when the penalty is small.

Keywords: periodic Markov decision process, periodic state, policy-iteration algorithm.

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Authors: Abdallah M. Abualkishik, Khairuddin Omar

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This article concerned with the translation of Quranic verses to Braille symbols, by using Visual basic program. The system has the ability to translate the special vibration for the Quran. This study limited for the (Noun + Scoon) vibrations. It builds on an existing translation system that combines a finite state machine with left and right context matching and a set of translation rules. This allows to translate the Arabic language from text to Braille symbols after detect the vibration for the Quran verses.

Keywords: Braille, Quran vibration, Finite State Machine.

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Authors: Manar AlJazzazi, Mohammed Rawashdeh, Tariq Alshawaheen, Aktham Malkawi

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This paper is a part of research, in which the way the biomedical engineers follow in their work is analyzed. The goal of this paper is to present a method for specification of user requirements in the medical devices maintenance process. Data Gathering Methods, Research Model Phases and Descriptive Analysis is presented. These technology and verification rules can be implemented in Medical devices maintenance management process to the maintenance process.

Keywords: Quality Function Deployment (QFD), User - requirements approach.

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Authors: Aaidha Hammad

Abstract:

The age a child to be exposed to a second language is a controversial issue in communities such as the Maldives where English is taught as a second language. It has been observed that different stakeholders have different viewpoints towards the issue. Some believe that the earlier children are exposed to a second language, the better they learn, while others disagree with the notion. Hence, this case study investigates whether children learn a second language better when they are exposed at an earlier age or not. The spoken and written data collected confirm that earlier exposure helps in mastering the sound pattern and speaking fluency with more native-like accent, while a later age is better for learning more abstract and concrete aspects such as grammar and syntactic rules.

Keywords: Age, development of language skills, fluency, second language acquisition.

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Authors: Zuzana Dideková, Beata Mikovičová

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Characterization of radio communication signals aims at automatic recognition of different characteristics of radio signals in order to detect their modulation type, the central frequency, and the level. Our purpose is to apply techniques used in image processing in order to extract pertinent characteristics. To the single analysis, we add several rules for checking the consistency of hypotheses using fuzzy logic. This allows taking into account ambiguity and uncertainty that may remain after the extraction of individual characteristics. The aim is to improve the process of radio communications characterization.

Keywords: fuzzy classification, fuzzy inference system, radio communication signals, telecommunications

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Authors: Ulrike Völlinger, Erik Lehmann, Rainer Stark

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The intention of this paper is, to help the user of evolutionary algorithms to adapt them easier to their problem at hand. For a lot of problems in the technical field it is not necessary to reach an optimum solution, but to reach a good solution in time. In many cases the solution is undetermined or there doesn-t exist a method to determine the solution. For these cases an evolutionary algorithm can be useful. This paper intents to give the user rules of thumb with which it is easier to decide if the problem is suitable for an evolutionary algorithm and how to design them.

Keywords: Multi criteria optimization, Memetic algorithms

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Authors: M. K. Holst, P. H. Kirkegaard, L. D. Christoffersen

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Present paper presents a parametric performancebased design model for optimizing hospital design. The design model operates with geometric input parameters defining the functional requirements of the hospital and input parameters in terms of performance objectives defining the design requirements and preferences of the hospital with respect to performances. The design model takes point of departure in the hospital functionalities as a set of defined parameters and rules describing the design requirements and preferences.

Keywords: Architectural Layout Design, Hospital Design, Parametric design, Performance-based models.

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Authors: Rosziati Ibrahim, Noraini Ibrahim

Abstract:

Unified Modeling Language (UML) is a standard language for modeling of a system. UML is used to visually specify the structure and behavior of a system. The system requirements are captured and then converted into UML specification. UML specification uses a set of rules and notations, and diagrams to specify the system requirements. In this paper, we present a tool for developing the UML specification. The tool will ease the use of the notations and diagrams for UML specification as well as increase the understanding and familiarity of the UML specification. The tool will also be able to check the conformance of the diagrams against each other for basic compliance of UML specification.

Keywords: Software Engineering, Unified Modeling Language (UML), UML Specification.

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Authors: Sandeep Kumar, R. B. Mishra

Abstract:

A large number of semantic web service composition approaches are developed by the research community and one is more efficient than the other one depending on the particular situation of use. So a close look at the requirements of ones particular situation is necessary to find a suitable approach to use. In this paper, we present a Technique Recommendation System (TRS) which using a classification of state-of-art semantic web service composition approaches, can provide the user of the system with the recommendations regarding the use of service composition approach based on some parameters regarding situation of use. TRS has modular architecture and uses the production-rules for knowledge representation.

Keywords: Classification, composition techniques, recommendation system, rule-based, semantic web service.

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Authors: Daniel Stamate

Abstract:

The paper presents an approach for handling uncertain information in deductive databases using multivalued logics. Uncertainty means that database facts may be assigned logical values other than the conventional ones - true and false. The logical values represent various degrees of truth, which may be combined and propagated by applying the database rules. A corresponding multivalued database semantics is defined. We show that it extends successful conventional semantics as the well-founded semantics, and has a polynomial time data complexity.

Keywords: Reasoning under uncertainty, multivalued logics, deductive databases, logic programs, multivalued semantics.

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Authors: Padmanabhan Balasubramanian, C. Ardil

Abstract:

An effective approach for realizing the binary tree structure, representing a combinational logic functionality with enhanced throughput, is discussed in this paper. The optimization in maximum operating frequency was achieved through delay minimization, which in turn was possible by means of reducing the depth of the binary network. The proposed synthesis methodology has been validated by experimentation with FPGA as the target technology. Though our proposal is technology independent, yet the heuristic enables better optimization in throughput even after technology mapping for such Boolean functionality; whose reduced CNF form is associated with a lesser literal cost than its reduced DNF form at the Boolean equation level. For cases otherwise, our method converges to similar results as that of [12]. The practical results obtained for a variety of case studies demonstrate an improvement in the maximum throughput rate for Spartan IIE (XC2S50E-7FT256) and Spartan 3 (XC3S50-4PQ144) FPGA logic families by 10.49% and 13.68% respectively. With respect to the LUTs and IOBUFs required for physical implementation of the requisite non-regenerative logic functionality, the proposed method enabled savings to the tune of 44.35% and 44.67% respectively, over the existing efficient method available in literature [12].

Keywords: Binary logic tree, FPGA based design, Boolean function, Throughput rate, CNF, DNF.

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