Showing papers in "Applied Mathematics & Information Sciences in 2016"
90 citations
TL;DR: The superiority of the continuous GA is seen in that it will alway s provide smooth and faster solutions as compared with the co nventional GA.
Abstract: In this paper, the solution of inverse kinematics problem of robot manipulators using genetic algorithms (GA) is presen ted. Two versions of genetic algorithms are used which include th e conventional GA and the continuous GA. The inverse kinemat ics problem is formulated as an optimization problem based on the concep t of minimizing the accumulative path deviation in the absen ce of any obstacles in the workspace. Simulation results show that th e continuous GA outperforms the conventional GA from all asp ects. The superiority of the continuous GA is seen in that it will alway s provide smooth and faster solutions as compared with the co nventional GA.
85 citations
46 citations
TL;DR: In this article, a new analytical technique for obta ing the analytical approximate solutions for system of Fredholm integral equations based on the use of the residual power series method (RPSM) is presented.
Abstract: In this paper, we present a new analytical technique for obta ining the analytical approximate solutions for system of Fredholm integral equations based on the use of the residual power series method (RPSM). The proposed method provides th e solution in terms of convergent series with easily computable compon ents, as well as it possesses main advantage as compared to ot her existed methods; it can be applied without any limitation or lineari z t on on the nature of the problem, type of classification, a nd the number of mesh points. In this sense, some examples are given to demons trate the simplicity and efficiency of the proposed method. T he results obtained by employing the RPSM are compared with exact solut ions to reveal that the method is easy to implement, straight forward and convenient to handle a wide range of such system of integr al quations.
41 citations
TL;DR: In this paper, a technique for order preference by similarity to ideal solution (TOPSIS) approach and extend the TOPSIS method to MCDM problem with single valued neutrosophic information is presented.
Abstract: The process of multiple criteria decision making (MCDM) is of determining the best choice among all of the probable alternatives. The problem of supplier selection on which decision maker has usually vague and imprecise knowledge is a typical example of multi criteria group decision-making problem. The conventional crisp techniques has not much effective for solving MCDM problems because of imprecise or fuzziness nature of the linguistic assessments. To find the exact values for MCDM problems is both difficult and impossible in more cases in real world. So, it is more reasonable to consider the values of alternatives according to the criteria as single valued neutrosophic sets (SVNS). This paper deal with the technique for order preference by similarity to ideal solution (TOPSIS) approach and extend the TOPSIS method to MCDM problem with single valued neutrosophic information. The value of each alternative and the weight of each criterion are characterized by single valued neutrosophic numbers. Here, the importance of criteria and alternatives is identified by aggregating individual opinions of decision makers (DMs) via single valued neutrosophic weighted averaging (IFWA) operator. The proposed method is, easy use, precise and practical for solving MCDM problem with single valued neutrosophic data. Finally, to show the applicability of the developed method, a numerical experiment for supplier choice is given as an application of single valued neutrosophic TOPSIS method at end of this paper.
39 citations
TL;DR: In this article, the authors proposed a methodology to numerically integrate functions using multicomplex algebras and their corresponding matrix representations, and investigated three different algorithms for various approximation strategies.
Abstract: In this paper, we propose a methodology to numerically integ rat functions using multicomplex algebras and their corresponding matrix representations. The methodology em ploys multicomplex Taylor series expansion (MCTSE) to adap tively approximate and integrate a function using sufficiently sma ll number of points. We investigate this methodology by pres enting three different algorithms for various approximation strategie s. We also use numerical studies to demonstrate the performa nce of the proposed methodology.
35 citations
TL;DR: This paper implements a relatively recent analytical method, called iterative reproducing kernel method (IRK M), to obtain a computational solution for fuzzy two-point boun dary value problem based on a generalized differentiabilit y concept.
Abstract: In this paper, we implement a relatively recent analytical t echnique, called iterative reproducing kernel method (IRK M), to obtain a computational solution for fuzzy two-point boun dary value problem based on a generalized differentiabilit y concept. The technique methodology is based on construct a solution in th e form of a rabidly convergent series with minimum size of cal culations using symbolic computation software. The proposed techniq ue s fully compatible with the complexity of such problem, w hile the obtained results are highly encouraging. Efficacious compu tational experiments are provided to guarantee the procedu re and to illustrate the theoretical statements of the present method in order to show its potentiality, generality and superiority for solv ing such fuzzy equation.
33 citations
TL;DR: This work presents an efficient method for voice pathology detection based on speech signal proc essing and machine learning techniques and exploits the simi larity function of the RBF kernel to separate the GMM models representing norma l and pathological voices.
Abstract: As acoustic signal generated from vocal folds is directly af fected by vocal tract pathologies, it can be an effective too l f r diagnosis purpose. In this work, we present an efficient meth od for voice pathology detection based on speech signal proc essing and machine learning techniques. In the proposed method, we use d MFCC to represent the signal features, and we chose to combi ne GMM and SVM classifiers to benefit from their generative and discr iminative natures respectively. That is to exploit the simi larity function of the RBF kernel to separate the GMM models representing norma l and pathological voices. To further improve the separatio n, we used modified versions of the well known Kullback-leibler and Bha ttacharyya distances. The modified distances, unlike the cl assical ones, do satisfy all metric axioms. As a result, we obtained an impr ovement of 2 % and 4 % in terms of sensitivity compared to using the classical Kullback-leibler and Bhattacharyya distances r espectively. The Receiver Operating Curve (ROC) does illus trate the efficiency of the proposed method.
30 citations
TL;DR: The goal of this paper is to provide a comprehensive review of approaches on determi ning the ”correct” number of clusters, and divides the approaches into three categories: internal measures, ext rnal measures, and clustering stability based methods.
Abstract: Clustering analysis seeks to partition a given dataset into groups or clusters so that the data objects within a cluster a re more similar to each other than the objects in different clusters . A very rich literature on clustering analysis has develope d over the past three decades. But a crucial question still remains unanswered: h ow many clusters are contained in the population on earth whe n only an observed set of samples is available? The goal of this paper i s to provide a comprehensive review of approaches on determi ning the ”correct” number of clusters. In particular, we divide thes e approaches into three categories: internal measures, ext rnal measures, and clustering stability based methods. Then, we introduce sev ral representative examples, and present specific challen ges pertinent to each category. Finally, the promising trends are suggested in this field.
26 citations
25 citations
TL;DR: In a previous work as discussed by the authors, we have presented an overview of the work of the Departamento de Matemática, Facultad de Ciencias, Univer sidad de los Andes, Mérida, Venezuela.
Abstract: 1 Departamento de matemática, Decanato de Ciencias y Tecnol ogı́a, Universidad Centroccidental Lisandro Alvarado, Ba rquisimeto, Venezuela 2 Departamento de matemática, Facultad de Ciencias, Univer sidad de los Andes, Mérida, Venezuela 3 Facultad de Ciencias Naturales y Matemática, Departament o de Matemática, Escuela Superior Politécnica del Litora l (ESPOL), Km 30.5 Vı́a Perimetral, Campus Gustavo Galindo, Guayaquil Ec uador..
TL;DR: In this paper, an optimal control problem for an SIR epidemic model with saturated incidence and saturated treatment was formulated, and two main efforts, namely treatment and vaccination, were considered.
Abstract: In this paper, we formulate an optimal control problem for an SIR epidemic model with saturated incidence and saturated treatment. Two main efforts, namely treatment and vaccination are considered ...
TL;DR: In this article, it was shown that the minimum of a differentiable harmonic c onvex function on the harmonic convex set can be characterized by the harmonic variational inequality.
Abstract: In this paper, we consider a new class of variational inequal ities, which is called the harmonic variational inequality . I is shown that that the minimum of a differentiable harmonic c onvex function on the harmonic convex set can be characteriz ed by the harmonic variational inequality. We use the auxiliary p inciple technique to discuss the existence of a solution of the harmonic variational inequality. Results proved in this paper may st imulate further research in this field.
TL;DR: In this article, the convergence of Bernstein polynomials has been studied in great detail and the concepts of statistical convergence of Berns t and VB−summability and related theorems have been introduced.
Abstract: The Bernstein operator is one of the important topics of appr oximation theory in which it has been studied in great detail s for a long time. The aim of this paper is to study the statistic al convergence of sequence of Bernstein polynomials. In thi s paper, we introduce the concepts of statistical convergence of Berns t in polynomials and VB−summability and related theorems. We also study Korovkin type-convergence of Bernstein polynomials.
TL;DR: This work proposes a new approach, which enables semantic web applications to access relation al databases and their contents by semantic methods and is effective for building ontology and important for mining semantic information fro m huge web resources.
Abstract: Semantic integration became an attractive area of research in several disciplines, such as information integration, d atabases and ontologies. Huge amount of data is still stored in relati onal databases (RDBs) that can be used to build ontology, and the atabase cannot be used directly by the semantic web. Therefore, one o f th main challenges of the semantic web is mapping relation l databases to ontologies (RDF(S)-OWL). Moreover, the use of manual wor k in the mapping of web contents to ontologies is impractical because it contains billions of pages and the most of these contents a re generated from relational databases. Hence, we propose a new pproach, which enables semantic web applications to access relation al databases and their contents by semantic methods. Domain ontologies can be used to formulate relational database schema and data in order to simplify the mapping (transformation) of the und erlying data sources. Our method consists of two main phases: building on tology from an RDB schema and the generation of ontology inst ances from an RDB data automatically. In the first phase, we studied fferent cases of RDB schema to be mapped into ontology repr es nted in RDF(S)-OWL, while in the second phase, the mapping rules a r used to transform RDB data to ontological instances repre s nt d in RDF triples. Our approach is demonstrated with examples, va lidated by ontology validator and implemented using Apache Jena in Java Language and MYSQL. This approach is effective for building ontology and important for mining semantic information fro m huge web resources.
TL;DR: Simulation results prove that PID controller parameters tu ned by ZN method for general aviation aircraft dynamics is be tter compared to the other methods in improving the stability and performance of flight in all conditions such as climb, cruise and appro ach phase.
Abstract: Today many aircraft control systems and process control ind ustries are employing classical controller such as Proport ional Integral Derivative Controller (PID) to improve the system characteristics and dynamic performance. To improve the st ability analysis and system performance of an aircraft, PID controller is emp loyed in this paper. The safety of flight envelope can be impro ved by tuning parameters of PID controller for pitch control dynam ics of an aircraft. Designing the mathematical model is nece ssary and important to describe the longitudinal pitch control of gen eral aviation aircraft system. PID controller is developed based on dynamic and mathematical modeling of an aircraft system. The variou s tuning methods such as Zeigler-Nichols method (ZN), Modifi e ZeiglerNichols method, TyreusLuyben tuning and Astrom-Hagglund tuning methods are evaluated for general aviation aircraft sys em. The simulation results prove that PID controller parameters tu ned by ZN method for general aviation aircraft dynamics is be tter compared to the other methods in improving the stability and performa nce of flight in all conditions such as climb, cruise and appro ach phase.
TL;DR: The numerical experiments show that the proposed algorithm, called HPSODEPSR, is a promising algorithm and can reach to the optimal or ne a optimal solution faster than the other comparative algorithms.
Abstract: In this paper, we present a new hybrid swarm optimization and differential evolution algorithm for solving constrained and engineering optimization problems. The proposed algorith m s called hybrid particle swarm optimization and differen tial evolution with population size reduction (HPSODEPSR). The powerful perfo rmance of any metaheuristics algorithm is measured by its ca pability to balance between the exploration and exploitation process. In the beginning of the search, the algorithm needs to explor e the search space with a large number of solutions in the population then during the search the need of the exploration process is redu ces while the need of the exposition process increases. From this poin t, we propose a population size reduction mechanism (PSRM), in PSRM, the proposed algorithm starts with a large number of solutio ns n the population and during the search the number of these solutions decreases after applying the greedy selection operator in o rder to remove the worst solutions from the population. Also , we propose a new automatic termination criterion which is called a prog ress vectorV. V is a (1× n) zero vector, wheren equal to the number of population partitions and contains of a number of subsets equal to the number of population reduction steps (partitio ns), when the population reduced, the corresponding subset value in V con verted to one. The algorithm terminates the search when all s ubsets values in the progress vector become ones. Moreover, we test the pro posed algorithm on eleven benchmark functions and five engin eri g optimization problems. We compare our proposed algorithm a gainst seven algorithms in order to investigate the general p rformance of it. The numerical experiments show that the proposed algori thm s a promising algorithm and can reach to the optimal or ne a optimal solution faster than the other comparative algorithms.
TL;DR: In this article, an estimation of the reflection of p-wave, T-wave and SV-wave on the boundary of a fiber-reinforced half-space of homogeneous, isotropic thermoelastic mediu m under effect of the relaxation times, magnetic field and rot ati n were taken into their consideration the boundary was stress-free as well as insulated.
Abstract: In this work, an estimation to study the reflection of p-wave, T-wave and SV-wave on the boundary of a fibre-reinforced half-space of homogeneous, isotropic thermoelastic mediu m under effect of the relaxation times, magnetic field and rot ati n were taken into our consideration the boundary was stress-free as well as insulated. GL model of generalized thermoelasticity which was known as the theory of thermoelasticity with two relaxation times, o r the theory of temperature-rate dependent thermoelastici ty has been applied to obtain the amplitudes of the reflection coefficients. Lame ’s potentials were used in the two dimensions oxz that tend to separate the governing equations into three equations that sought in har monic travelling form. We estimated the equation of the velo cities of p-wave, T-wave and SV-wave. The boundary conditions for the mechani al and Maxwell’s stresses and the thermal insulated at the b oundary are applied to determine the reflection coefficients of the lo ngitudinal p-wave and thermal T-wave as well as the transver se wave SVand conclude them some special cases. Will arrive at the resu lts of the research proposal consistent with the classic res ults. The results obtained are calculated numerically by taking an appropria te metal and presented graphically.
TL;DR: The novel hybrid algorithms are applied to solve 15 bench mark functions chosen from literature and confirm the effective ness of the proposed algorithms in solving various benchmark optimiza tion functions.
Abstract: In this paper, two hybrid schemes using cuckoo search algori thm and genetic algorithm are proposed. In the two hybrid schemes, the algorithm consists of two phases in the first pha e, CS (or GA) explores the search space. In the second phase, to improve global search and get rid of trapping into several local opti ma. The novel hybrid algorithms are applied to solve 15 bench mark functions chosen from literature. The simulation results and compari son with classical CS and GA algorithms confirm the effective ness of the proposed algorithms in solving various benchmark optimiza tion functions.
TL;DR: Entropy analysis of two test images shows that randomness of the ciphered images with the proposed key schemes are more ra ndom than in case of the ECPRNG without modulation by a chaotic map.
Abstract: Pseudo-random number sequences which using the form of elli ptic curves can be generated efficiently in software or hardware by the same methods that are used for the implementa tion of elliptic curve (EC) public-key cryptosystems. In th is paper, we proposed a secure image encryption scheme using key sequenc s generated from Chaos-Driven Elliptic Curve Pseudo-rand om Number Generator (C-D ECPRNG). This key sequences derived from ran dom sequences based on EC points operations driven by a chaot ic map. These constructions improve randomness properties of the generated sequences since it combines good statistical properties of an ECPRNG and a Chaotic Pseudo-random Number Generator (CPRNG ). Entropy analysis of two test images shows that randomness of the ciphered images with the proposed key schemes are more ra ndom than in case of the ECPRNG without modulation by a chaoti c map. Statistical and differential analysis demonstrate th at the proposed schemes have adequate security for the confid entiality of digital images and the encryption is efficient compared to other comp etitive algorithms.
TL;DR: Brajesh Kumar Singh and Carlo Bianca as mentioned in this paper have studied at the Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India.
Abstract: Brajesh Kumar Singh 1 and Carlo Bianca2,∗ 1 Department of Applied Mathematics, School of Allied Scienc s, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pr desh 226025, India 2 Laboratoire de Physique Statistique, Ecole Normale Supér ieure, PSL Research University; Université Paris Diderot S rbonne ParisCité; Sorbonne Universités UPMC Univ Paris 06; CNRS; 24 ru e Lhomond, 75005 Paris, France