Log in

Relevant bibliographies by topics / Modeling algorithms / Journal articles

Journal articles on the topic 'Modeling algorithms'

To see the other types of publications on this topic, follow the link: Modeling algorithms.

Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Modeling algorithms.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Barbulescu, L., A. E. Howe, L. D. Whitley, and M. Roberts. "Understanding Algorithm Performance on an Oversubscribed Scheduling Application." Journal of Artificial Intelligence Research 27 (December 28, 2006): 577–615. http://dx.doi.org/10.1613/jair.2038.

Full text

Abstract:

The best performing algorithms for a particular oversubscribed scheduling application, Air Force Satellite Control Network (AFSCN) scheduling, appear to have little in common. Yet, through careful experimentation and modeling of performance in real problem instances, we can relate characteristics of the best algorithms to characteristics of the application. In particular, we find that plateaus dominate the search spaces (thus favoring algorithms that make larger changes to solutions) and that some randomization in exploration is critical to good performance (due to the lack of gradient information on the plateaus). Based on our explanations of algorithm performance, we develop a new algorithm that combines characteristics of the best performers; the new algorithm's performance is better than the previous best. We show how hypothesis driven experimentation and search modeling can both explain algorithm performance and motivate the design of a new algorithm.

APA, Harvard, Vancouver, ISO, and other styles

2

Agapie, Alexandru. "Theoretical Analysis of Mutation-Adaptive Evolutionary Algorithms." Evolutionary Computation 9, no. 2 (June 2001): 127–46. http://dx.doi.org/10.1162/106365601750190370.

Full text

Abstract:

Adaptive evolutionary algorithms require a more sophisticated modeling than their static-parameter counterparts. Taking into account the current population is not enough when implementing parameter-adaptation rules based on success rates (evolution strategies) or on premature convergence (genetic algorithms). Instead of Markov chains, we use random systems with complete connections - accounting for a complete, rather than recent, history of the algorithm's evolution. Under the new paradigm, we analyze the convergence of several mutation-adaptive algorithms: a binary genetic algorithm, the 1/5 success rule evolution strategy, a continuous, respectively a dynamic (1+1) evolutionary algorithm.

APA, Harvard, Vancouver, ISO, and other styles

3

Merkle, Daniel, and Martin Middendorf. "Modeling the Dynamics of Ant Colony Optimization." Evolutionary Computation 10, no. 3 (September 2002): 235–62. http://dx.doi.org/10.1162/106365602760234090.

Full text

Abstract:

The dynamics of Ant Colony Optimization (ACO) algorithms is studied using a deterministic model that assumes an average expected behavior of the algorithms. The ACO optimization metaheuristic is an iterative approach, where in every iteration, artificial ants construct solutions randomly but guided by pheromone information stemming from former ants that found good solutions. The behavior of ACO algorithms and the ACO model are analyzed for certain types of permutation problems. It is shown analytically that the decisions of an ant are influenced in an intriguing way by the use of the pheromone information and the properties of the pheromone matrix. This explains why ACO algorithms can show a complex dynamic behavior even when there is only one ant per iteration and no competition occurs. The ACO model is used to describe the algorithm behavior as a combination of situations with different degrees of competition between the ants. This helps to better understand the dynamics of the algorithm when there are several ants per iteration as is always the case when using ACO algorithms for optimization. Simulations are done to compare the behavior of the ACO model with the ACO algorithm. Results show that the deterministic model describes essential features of the dynamics of ACO algorithms quite accurately, while other aspects of the algorithms behavior cannot be found in the model.

APA, Harvard, Vancouver, ISO, and other styles

4

Merheb, Abdel-Razzak, Hassan Noura, and François Bateman. "Mathematical Modeling of Ecological Systems Algorithm." Lebanese Science Journal 22, no. 2 (March 2, 2022): 209–31. http://dx.doi.org/10.22453/lsj-022.2.209-231.

Full text

Abstract:

In this paper, the mathematical modeling of a new bio-inspired evolutionary search algorithm called Ecological Systems Algorithm (ESA) is presented. ESA imitates ecological rules to find iteratively the optimum of a given function through interaction between predator and prey search species. ESA is then compared to the well-known Genetic Algorithm which is a powerful bio-inspired stochastic search/optimization algorithm used for decades. Simulation results of the two algorithms optimizing ten different benchmark functions are used to investigate and compare both algorithms based on their speed, performance, reliability, and efficiency.

APA, Harvard, Vancouver, ISO, and other styles

5

Beattie, Ian D. "Modeling Operations and Algorithms." Arithmetic Teacher 33, no. 6 (February 1986): 23–28. http://dx.doi.org/10.5951/at.33.6.0023.

Full text

Abstract:

The idea of using manipulative materials to model operation and algorithms is not new. The Arithmetic Teacher frequently includes articles on the topic, and its readers should have accumulated a wealth of excellent teaching suggestions. Current methodology books and school texts place great emphasis on the use of manipulatives. Thus one might expect appropriate manipulative materials to be a mainstay of every mathematics classroom, but evidence suggests otherwise. Although teachers believe that manipulative materials should be used for mathematics instruction and that the usc of such materials does develop understanding, the use of manipulative materials diminishes through the grade (Suydam 1984a).

APA, Harvard, Vancouver, ISO, and other styles

6

Vose, Michael D. "Modeling Simple Genetic Algorithms." Evolutionary Computation 3, no. 4 (December 1995): 453–72. http://dx.doi.org/10.1162/evco.1995.3.4.453.

Full text

Abstract:

The infinite- and finite-population models of the simple genetic algorithm are extended and unified, The result incorporates both transient and asymptotic GA behavior. This leads to an interpretation of genetic search that partially explains population trajectories. In particular, the asymptotic behavior of the large-population simple genetic algorithm is analyzed.

APA, Harvard, Vancouver, ISO, and other styles

7

Li, Jing Zhu, Qian Li, Tai Yu Liu, and Wei Hong Niu. "Data Mining: Modeling, Algorithms, Applications and Systems." Advanced Materials Research 926-930 (May 2014): 2786–89. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.2786.

Full text

Abstract:

Data mining is a multidisciplinary field of the 20th century gradually, this paper based on data mining modeling, algorithms, applications and software tools were reviewed, the definition of data mining, the scope and characteristics of the data sets and data mining various practical situations; summarizes the data mining in the practical application of the basic steps and processes; data mining tasks in a variety of applications and modeling issues were discussed; cited the current field of data mining is mainly popular algorithms, and algorithm design issues to consider briefly analyzed; overview of the current data mining algorithm in a number of areas; more comprehensive description of the current performance and data mining software tools developer circumstances; Finally, the development of data mining prospects and direction prospected.

APA, Harvard, Vancouver, ISO, and other styles

8

STEWART, A. JAMES. "LOCAL ROBUSTNESS AND ITS APPLICATION TO POLYHEDRAL INTERSECTION." International Journal of Computational Geometry & Applications 04, no. 01 (March 1994): 87–118. http://dx.doi.org/10.1142/s0218195994000070.

Full text

Abstract:

The field of solid modeling makes extensive ve use of a variety of geometric algorithms. When implemented on a computer, these algorithms often fail because the computer only provides floating point arithmetic, while the algorithms are expecting infinite precision arithmetic on real numbers. These algorithms are not robust. This paper presents a formal theory of robustness. It is then argued that the elegant theoretical approach to robustness is not viable in practice: algorithms like those used in solid modeling are generally too complex for this approach. This paper presents a practical alternative to the formal theory of robustness; this alternative is called local robustness. Local robustness is applied to the design of a polyhedral intersection algorithm, which is an important component in many solid modelers. The intersection algorithm has been implemented, and, in extensive tests, has never failed to produce a valid polyhedron of intersection. A concise characterization of the locally robust intersection algorithm is presented; this characterization can be used to develop variants of the intersection algorithm, and to develop robust versions of other solid modeling algorithms.

APA, Harvard, Vancouver, ISO, and other styles

9

Wang, Yang, Shi Jun Ji, and Li Jun Yang. "General Subdivision Inferred from Catmull-Clark Subdivision Algorithm." Materials Science Forum 532-533 (December 2006): 789–92. http://dx.doi.org/10.4028/www.scientific.net/msf.532-533.789.

Full text

Abstract:

Subdivision algorithms have emerged recently as a powerful and useful technique in modeling free-form surfaces. Subdivision algorithms exited at present however, being their disadvantages, can’t meet the demand of wide application in modeling surfaces and don’t still belong to a general theory. In this paper, a general subdivision algorithm is presented which is a general conclusion inferred from classical Catmull-Clark subdivision algorithm and can produce existing subdivision algorithm by selecting reasonable vertical weights and horizontal weights. The subdivision algorithm is an ideal resolution for keeping shape feature such as crease, corner and dart contrast to all existing subdivision algorithms, it also have the advantage of flexible weights selection, easily control of shape and high compute speed. Therefore, the algorithms are extensively applicable for shape modeling in computer aided geometric design, industrial prototype design and reverse engineering.

APA, Harvard, Vancouver, ISO, and other styles

10

Potapov, Viktor S., and Sergei M. Gushansky. "Development of a technique for modeling entangled quantum computations that are applicable in Simon’s quantum algorithm." Informatization and communication, no. 3 (May 5, 2020): 66–70. http://dx.doi.org/10.34219/2078-8320-2020-11-3-66-70.

Full text

Abstract:

This paper describes the basics of developing quantum algorithms and modeling entangled quantum computations applicable in quantum algorithms. Quantum algorithms involve the use of vector and matrix algebra. The basic tasks of the simulation proposed in the work are determined within the framework of the algorithm for executing quantum algorithms, taking into account entanglement. A technique has been developed for modeling entangled quantum calculations applicable in the Simon quantum algorithm, which helps to predict the behavior of the quantum algorithm (or any other computing process that proceeds as part of the work of a quantum computer system) with partial entanglement.

APA, Harvard, Vancouver, ISO, and other styles

11

Korkmaz Tan, Rabia, and Şebnem Bora. "Adaptive parameter tuning for agent-based modeling and simulation." SIMULATION 95, no. 9 (June 25, 2019): 771–96. http://dx.doi.org/10.1177/0037549719846366.

Full text

Abstract:

The purpose of this study was to solve the parameter-tuning problem of complex systems modeled in an agent-based modeling and simulation environment. As a good set of parameters is necessary to demonstrate the target behavior in a realistic way, modeling a complex system constitutes an optimization problem that must be solved for systems with large parameter spaces. This study presents a three-step hybrid parameter-tuning approach for agent-based models and simulations. In the first step, the problem is defined; in the second step, a parameter-tuning process is performed using the following meta-heuristic algorithms: the Genetic Algorithm, the Firefly Algorithm, the Particle Swarm Optimization algorithm, and the Artificial Bee Colony algorithm. The critical parameters of the meta-heuristic algorithms used in the second step are tuned using the adaptive parameter-tuning method. Thus, new meta-heuristic algorithms are developed, namely, the Adaptive Genetic Algorithm, the Adaptive Firefly Algorithm, the Adaptive Particle Swarm Optimization algorithm, and the Adaptive Artificial Bee Colony algorithm. In the third step, the control phase, the algorithm parameters obtained via the adaptive parameter-tuning method and the parameter values of the model obtained from the meta-heuristic algorithms are manually provided to the developed tool performing the parameter-tuning process and they are tested. The best results are achieved when the meta-heuristic algorithms that were successful in the optimization process are used with their critical parameters adjusted for optimum results. The proposed approach is tested by using the Predator–Prey model, the Eight Queens model, and the Flow Zombies model, and the results are compared.

APA, Harvard, Vancouver, ISO, and other styles

12

Shi, Heng Hua, Xin Xu, Yu Jie Wang, and Yuan Yue Yang. "Research on Queue Scheduling Algorithm Modeling and Analysis." Advanced Materials Research 542-543 (June 2012): 1390–93. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.1390.

Full text

Abstract:

With the development of network technology and the wide use of the Internet, QoS has attracted wide attention. Queue scheduling algorithm of Router is an important core technology of the network resource management for QoS. Through controlling usage of the link bandwidth of the different type groups, the different traffics have the different levels of service. Based on the analysis and modeling of FIFO, PQ, and WFQ scheduling algorithms, the simulation experiment simulate three different priority video conferencing traffic, and apply FIFO, PQ, and WFQ scheduling algorithms on the bottleneck link. The simulation results compare network delay of FIFO, PQ, and WFQ scheduling algorithms, and describe the various queue scheduling algorithm characteristics.

APA, Harvard, Vancouver, ISO, and other styles

13

Hamim, Touria, Faouzia Benabbou, and Nawal Sael. "Student Profile Modeling Using Boosting Algorithms." International Journal of Web-Based Learning and Teaching Technologies 17, no. 5 (September 2022): 1–13. http://dx.doi.org/10.4018/ijwltt.20220901.oa4.

Full text

Abstract:

The student profile has become an important component of education systems. Many systems objectives, as e-recommendation, e-orientation, e-recruitment and dropout prediction are essentially based on the profile for decision support. Machine learning plays an important role in this context and several studies have been carried out either for classification, prediction or clustering purpose. In this paper, the authors present a comparative study between different boosting algorithms which have been used successfully in many fields and for many purposes. In addition, the authors applied feature selection methods Fisher Score, Information Gain combined with Recursive Feature Elimination to enhance the preprocessing task and models’ performances. Using multi-label dataset predict the class of the student performance in mathematics, this article results show that the Light Gradient Boosting Machine (LightGBM) algorithm achieved the best performance when using Information gain with Recursive Feature Elimination method compared to the other boosting algorithms.

APA, Harvard, Vancouver, ISO, and other styles

14

Pehlivanoglu, Volkan Yasin. "Double surrogate modeling usage in PSO." Aircraft Engineering and Aerospace Technology 89, no. 6 (October 2, 2017): 862–70. http://dx.doi.org/10.1108/aeat-02-2015-0035.

Full text

Abstract:

Purpose The purpose of this paper is to improve the efficiency of particle optimization method by using direct and indirect surrogate modeling in inverse design problems. Design/methodology/approach The new algorithm emphasizes the use of a direct and an indirect design prediction based on local surrogate models in particle swarm optimization (PSO) algorithm. Local response surface approximations are constructed by using radial basis neural networks. The principal role of surrogate models is to answer the question of which individuals should be placed into the next swarm. Therefore, the main purpose of surrogate models is to predict new design points instead of estimating the objective function values. To demonstrate its merits, the new approach and six comparative algorithms were applied to two different test cases including surface fitting of a geographical terrain and an inverse design of a wing, the averaged best-individual fitness values of the algorithms were recorded for a fair comparison. Findings The new algorithm provides more than 60 per cent reduction in the required generations as compared with comparative algorithms. Research limitations/implications The comparative study was carried out only for two different test cases. It is possible to extend test cases for different problems. Practical implications The proposed algorithm can be applied to different inverse design problems. Originality/value The study presents extra ordinary application of double surrogate modeling usage in PSO for inverse design problems.

APA, Harvard, Vancouver, ISO, and other styles

15

Shah, Avdhi, Urvi Shah, Tilak Satra, and Purva Raut. "Comparison of Topic Modeling Algorithms." INTERNATIONAL JOURNAL OF RECENT TRENDS IN ENGINEERING & RESEARCH 05, no. 11 (November 30, 2019): 18–22. http://dx.doi.org/10.23883/ijrter.2019.5093.bmclg.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Mathieu, Anne. "Dynamical Modeling using Evolutionary Algorithms." Symposium - International Astronomical Union 220 (2004): 329–30. http://dx.doi.org/10.1017/s007418090018355x.

Full text

Abstract:

I will present a new method of dynamical modeling of stellar systems based on evolutionary algorithms. the technique will be illustrated with an application to the problem of recovering the gravitational potential of a thin galactic disc from kinematic observables in a non-parametric way.

APA, Harvard, Vancouver, ISO, and other styles

17

Morgan, R., and M. Gallagher. "Using Landscape Topology to Compare Continuous Metaheuristics: A Framework and Case Study on EDAs and Ridge Structure." Evolutionary Computation 20, no. 2 (June 2012): 277–99. http://dx.doi.org/10.1162/evco_a_00070.

Full text

Abstract:

In this paper we extend a previously proposed randomized landscape generator in combination with a comparative experimental methodology to study the behavior of continuous metaheuristic optimization algorithms. In particular, we generate two-dimensional landscapes with parameterized, linear ridge structure, and perform pairwise comparisons of algorithms to gain insight into what kind of problems are easy and difficult for one algorithm instance relative to another. We apply this methodology to investigate the specific issue of explicit dependency modeling in simple continuous estimation of distribution algorithms. Experimental results reveal specific examples of landscapes (with certain identifiable features) where dependency modeling is useful, harmful, or has little impact on mean algorithm performance. Heat maps are used to compare algorithm performance over a large number of landscape instances and algorithm trials. Finally, we perform a meta-search in the landscape parameter space to find landscapes which maximize the performance between algorithms. The results are related to some previous intuition about the behavior of these algorithms, but at the same time lead to new insights into the relationship between dependency modeling in EDAs and the structure of the problem landscape. The landscape generator and overall methodology are quite general and extendable and can be used to examine specific features of other algorithms.

APA, Harvard, Vancouver, ISO, and other styles

18

Hamou, Reda Mohamed, Abdelmalek Amine, Ali Rahmouni, Ahmed Chaouki Lokbani, and Michel Simonet. "Modeling of Inclusion by Genetic Algorithms." International Journal of Chemoinformatics and Chemical Engineering 3, no. 1 (January 2013): 19–36. http://dx.doi.org/10.4018/ijcce.2013010103.

Full text

Abstract:

The Cyclodextrins are of particular interest and importance in the field of inclusion and the formation of molecular complex. The aim of this work is to search by various techniques, among others: the molecular docking, the inclusion techniques, and complexations (Tail-Thread, Thread-Thread, Tail-Tail) of conformations (geometric parameters) to form inclusion complexes of beta-cyclodextrin with triphenylphosphine using an evolutionary optimization method in this case the Genetic Algorithms. The results are satisfactory. Software was designed to find an elite generation that represents the most stable complexes (minimum energy). This energy has been a determining factor and was chosen as fitness function (fitness) of the genetic algorithm.

APA, Harvard, Vancouver, ISO, and other styles

19

PRUSINKIEWICZ, PRZEMYSLAW, MITRA SHIRMOHAMMADI, and FARAMARZ SAMAVATI. "L-SYSTEMS IN GEOMETRIC MODELING." International Journal of Foundations of Computer Science 23, no. 01 (January 2012): 133–46. http://dx.doi.org/10.1142/s0129054112400096.

Full text

Abstract:

We show that parametric context-sensitive L -systems with affine geometry interpretation provide a succinct description of some of the most fundamental algorithms of geometric modeling of curves. Examples include the Lane-Riesenfeld algorithm for generating B -splines, the de Casteljau algorithm for generating Bézier curves, and their extensions to rational curves. Our results generalize the previously reported geometric-modeling applications of L -systems, which were limited to subdivision curves.

APA, Harvard, Vancouver, ISO, and other styles

20

Afrakoti, Iman E. P., and Vahdat Nazerian. "Performance Analysis of Optimization Process on Adaptive Group of Ink Drop Spread Algorithm Proficiency." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 6 (November 4, 2020): 918–24. http://dx.doi.org/10.2174/2352096512666191127122752.

Full text

Abstract:

Aims: Two evolutionary algorithms consist of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are being used for finding the best value of critical parameters in AGIDS which will affect the accuracy and efficiency of the algorithm. Background: Adaptive Group of Ink Drop Spread (AGIDS) is a powerful algorithm which was proposed in fuzzy domain based on Active Learning Method (ALM) algorithm. Objective: The effectiveness of AGIDS vs. artificial neural network and other soft-computing algorithms has been shown in classification, system modeling and regression problems. Methods: For solving a real-world problem a tradeoff should be taken between the needed accuracy and the available time and processing resources. Results: The simulation result shows that optimization approach will affect the accuracy of modelling being better, but its computation time is rather high. Conclusion: The simulation shows that AGIDS algorithm has a suitable efficacy in solving complex problems without using complex optimization algorithms. Other: The simulation shows that AGIDS algorithm has a suitable efficacy in solving complex problems without using complex optimization algorithms.

APA, Harvard, Vancouver, ISO, and other styles

21

Martínez, Rogelio, Erik Zamora, Humberto Sossa, Fernando Arce, and Luis Arturo Soriano. "Orientation Modeling Using Quaternions and Rational Trigonometry." Machines 10, no. 9 (August 30, 2022): 749. http://dx.doi.org/10.3390/machines10090749.

Full text

Abstract:

In recent years, the recreational and commercial use of flight and driving simulators has become more popular. All these applications require the calculation of orientation in either two or three dimensions. Besides the Euler angles notation, other alternatives to represent rigid body rotations include axis-angle notation, homogeneous transformation matrices, and quaternions. All these methods involve transcendental functions in their calculations, which represents a disadvantage when these algorithms are implemented in hardware. The use of transcendental functions in software-based algorithms may not represent a significant disadvantage, but in hardware-based algorithms, the potential of rational models stands out. Generally, to calculate transcendental functions in hardware, it is necessary to utilize algorithms based on the CORDIC algorithm, which requires a significant amount of hardware resources (parallel) or the design of a more complex control unit (pipelined). This research presents a new procedure for model orientation using rational trigonometry and quaternion notation, avoiding trigonometric functions for calculations. We describe the orientation of a gimbal mechanism presented in many applications, from autonomous vehicles such as cars or drones to industrial manipulators. This research aims to compare the efficiency of a rational implementation to classical modeling using the techniques mentioned above. Furthermore, we simulate the models with software tools and propose a hardware architecture to implement our algorithms.

APA, Harvard, Vancouver, ISO, and other styles

22

García-Martín, Eva, Albert Bifet, and Niklas Lavesson. "Energy modeling of Hoeffding tree ensembles." Intelligent Data Analysis 25, no. 1 (January 26, 2021): 81–104. http://dx.doi.org/10.3233/ida-194890.

Full text

Abstract:

Energy consumption reduction has been an increasing trend in machine learning over the past few years due to its socio-ecological importance. In new challenging areas such as edge computing, energy consumption and predictive accuracy are key variables during algorithm design and implementation. State-of-the-art ensemble stream mining algorithms are able to create highly accurate predictions at a substantial energy cost. This paper introduces the nmin adaptation method to ensembles of Hoeffding tree algorithms, to further reduce their energy consumption without sacrificing accuracy. We also present extensive theoretical energy models of such algorithms, detailing their energy patterns and how nmin adaptation affects their energy consumption. We have evaluated the energy efficiency and accuracy of the nmin adaptation method on five different ensembles of Hoeffding trees under 11 publicly available datasets. The results show that we are able to reduce the energy consumption significantly, by 21% on average, affecting accuracy by less than one percent on average.

APA, Harvard, Vancouver, ISO, and other styles

23

Watanabe, Toshihiko, Takeshi Kamai, and Tomoki Ishimaru. "Robust Estimation of Camera Homography by Fuzzy RANSAC Algorithm with Reinforcement Learning." Journal of Advanced Computational Intelligence and Intelligent Informatics 19, no. 6 (November 20, 2015): 833–42. http://dx.doi.org/10.20965/jaciii.2015.p0833.

Full text

Abstract:

The computer vision approach involves many modeling problems in preventing noise caused by sensing units such as cameras and projectors. To improve computer vision modeling performance, a robust modeling technique must be developed for essential models in the system. The RANSAC and LMedS algorithms have been widely applied in such issues, but performance deteriorates as the noise ratio increases and the calculation time for algorithms tends to increase in actual applications. In this study, we propose a new fuzzy RANSAC algorithm for homography estimation based on the reinforcement learning concept. The performance of the algorithm is evaluated by modeling synthetic data and camera homography experiments. Their results found the method to be effective in improving calculation time, model optimality, and robustness in modeling performance.

APA, Harvard, Vancouver, ISO, and other styles

24

Chen, Yuzhong, Zhenyu Liu, Yulin Liu, and Chen Dong. "Distributed Attack Modeling Approach Based on Process Mining and Graph Segmentation." Entropy 22, no. 9 (September 14, 2020): 1026. http://dx.doi.org/10.3390/e22091026.

Full text

Abstract:

Attack graph modeling aims to generate attack models by investigating attack behaviors recorded in intrusion alerts raised in network security devices. Attack models can help network security administrators discover an attack strategy that intruders use to compromise the network and implement a timely response to security threats. However, the state-of-the-art algorithms for attack graph modeling are unable to obtain a high-level or global-oriented view of the attack strategy. To address the aforementioned issue, considering the similarity between attack behavior and workflow, we employ a heuristic process mining algorithm to generate the initial attack graph. Although the initial attack graphs generated by the heuristic process mining algorithm are complete, they are extremely complex for manual analysis. To improve their readability, we propose a graph segmentation algorithm to split a complex attack graph into multiple subgraphs while preserving the original structure. Furthermore, to handle massive volume alert data, we propose a distributed attack graph generation algorithm based on Hadoop MapReduce and a distributed attack graph segmentation algorithm based on Spark GraphX. Additionally, we conduct comprehensive experiments to validate the performance of the proposed algorithms. The experimental results demonstrate that the proposed algorithms achieve considerable improvement over comparative algorithms in terms of accuracy and efficiency.

APA, Harvard, Vancouver, ISO, and other styles

25

GALKA, ANDREAS, KEVIN K. F. WONG, ULRICH STEPHANI, TOHRU OZAKI, and MICHAEL SINIATCHKIN. "BLIND SIGNAL SEPARATION OF MIXTURES OF CHAOTIC PROCESSES: A COMPARISON BETWEEN INDEPENDENT COMPONENT ANALYSIS AND STATE SPACE MODELING." International Journal of Bifurcation and Chaos 23, no. 10 (October 2013): 1350165. http://dx.doi.org/10.1142/s0218127413501654.

Full text

Abstract:

We perform a systematic comparison between different algorithms for solving the Blind Signal Separation problem. In particular, we compare five well-known algorithms for Independent Component Analysis (ICA) with a recently proposed algorithm based on linear state space modeling (IC–LSS). The comparison is based on simulated mixtures of six source signals, five of which are generated by nonlinear deterministic processes evolving on chaotic attractors. The quality of the reconstructed sources is quantified by two measures, one based on a distance measure implemented by a Frobenius norm, and one based on residual mutual information. We find that the IC–LSS modeling algorithm offers several advantages over the ICA algorithms: it succeeds in unmixing Gaussian sources, on short time series it performs, on average, better than static ICA algorithms, it does not try to remove coincidental dependencies resulting from finite data set size, and it shows the potential to reconstruct the sources even in the case of noninvertible mixing. As expected, for the case of non-Gaussian sources, invertible mixing and sufficient time series length, the ICA algorithms typically outperform IC–LSS modeling.

APA, Harvard, Vancouver, ISO, and other styles

26

Zarevich, Anton, F. Makarenko, A. Yagodkin, and Konstantin Zolnikov. "Modeling the behavior of mobile robots using genetic algorithms." Modeling of systems and processes 15, no. 3 (October 5, 2022): 7–16. http://dx.doi.org/10.12737/2219-0767-2022-15-3-7-16.

Full text

Abstract:

The article is devoted to the analysis of the behavior of a mobile robot using finite state machine algorithms in order to find a way to the goal and avoid obstacles. After justifying the use of such methods, the analysis of a standard deterministic finite automaton is done. Further, the theory of Markov processes is applied to this algorithm, as a result of which the state machine becomes part of the hidden Markov model. This allows you to apply probabilistic methods to modeling the behavior of the robot. This probabilistic behavior is most promising in complex environments with unpredictable obstacle configurations. To compare the efficiency of deterministic and probabilistic finite state machine, we applied a genetic algorithm. In the numerical experiment that we conducted in the Scilab software, we considered two main types of environments in which a mobile robot can move - an office-type environment and a polygonal-type environment. For each type of environment, we alternately applied each of the indicated behavior algorithms. For the genetic algorithm, we used one hundred individuals who were trained over 1000 generations to find the most optimal path in the specified environments. As a result, it was found that the deterministic finite state machine algorithm is the most promising for movement in an office-type environment, and the probabilistic finite state machine algorithm gives the best result in a complex polygonal environment.

APA, Harvard, Vancouver, ISO, and other styles

27

Miao, Zhi Nong, and Hui Jun Zheng. "An Improved Back-Propagation Algorithm for Fuzzy Modeling." Applied Mechanics and Materials 48-49 (February 2011): 198–202. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.198.

Full text

Abstract:

Fuzzy modeling is discussed in many literatures and there are numerous algorithms are proposed. Back-propagation algorithm is an efficient algorithm for fuzzy modeling and many papers proposed the usage of such method. But there exists potential risk of dead zone, abrupt inference surface and decreasing sensitivity for normal back-propagation algorithm in fuzzy modeling. This paper analysis the potential problems of normal algorithm and suggest a reformative back-propagation algorithm for fuzzy modeling. A complete algorithm is presented in the paper and some simulate result is discussed

APA, Harvard, Vancouver, ISO, and other styles

28

Bushmakova, Maria А., and Elena V. Kustova. "Modeling vibrational relaxation rate using machine learning methods." Vestnik of Saint Petersburg University. Mathematics. Mechanics. Astronomy 9, no. 1 (2022): 113–25. http://dx.doi.org/10.21638/spbu01.2022.111.

Full text

Abstract:

The aim of the present study is to develop an efficient algorithm for simulating nonequilibrium gas-dynamic problems using the detailed state-to-state approach for vibrationalchemical kinetics. Optimization of the vibrational relaxation rate computation using machine learning algorithms is discussed. Since traditional calculation methods require a large number of operations, time and memory, it is proposed to predict the relaxation rates instead of explicit calculations. K-nearest neighbour and histogram based gradient boosting algorithms are applied. The algorithms were trained on datasets obtained using two classical models for the rate coefficients: the forced harmonic oscillator model and that of Schwartz-Slawsky-Herzfeld. Trained algorithms were used to solve the problem of spatially homogeneous relaxation of the O2-O mixture. Comparison of accuracy and calculation time by different methods is carried out. It is shown that the proposed algorithms allow one to predict the relaxation rates with good accuracy and to solve approximately the set of governing equations for the fluid-dynamic variables. Thus, we can recommend the use of machine learning methods in nonequilibrium gas dynamics coupled with detailed vibrational-chemical kinetics. The ways of further optimization of the considered methods are discussed.

APA, Harvard, Vancouver, ISO, and other styles

29

Cinque, Marcello, and Catello Di Martino. "Adaptive Modeling of Routing Algorithms for Wireless Sensor Networks." International Journal of Adaptive, Resilient and Autonomic Systems 1, no. 1 (January 2010): 21–40. http://dx.doi.org/10.4018/jaras.2010071702.

Full text

Abstract:

Recent years have witnessed a proliferation of routing algorithms for Wireless Sensor Networks (WSNs), hence complicating the choice of the proper algorithm to be used for a given application. Simulation frameworks represent a viable solution to anticipate crucial choices, however existing solutions do not encompass the impact of changes (e.g., route updates, node crashes) on the nodes behavior and vice-versa. This article proposes a novel adaptive modeling approach to master the complexity of the thorough simulation of routing algorithms for WSN. Experimental results are provided showing the effectiveness of the proposed approach at managing changes, and dealing with detailed aspects, during the simulation and comparison of several routing algorithms.

APA, Harvard, Vancouver, ISO, and other styles

30

Krupenev, Dmitry, Denis Boyarkin, and Dmitrii Iakubovskii. "Factoring in scheduled repairs of generating units when assessing the resource adequacy of electric power systems." E3S Web of Conferences 139 (2019): 01018. http://dx.doi.org/10.1051/e3sconf/201913901018.

Full text

Abstract:

This study presents the algorithms for modeling of scheduled repairs of generating equipment when assessing the resource adequacy of electric power systems by the Monte Carlo method that relies on random events. We present an analysis of the algorithms adopted in the available software and computer systems used to assess the resource adequacy and highlight their shortcomings. We propose an algorithm for modeling of scheduled repairs of generating units that does away with the flaws of the algorithms adopted elsewhere. In the final part of the article, we present the findings of numerical experiments that test the performance of the algorithms.

APA, Harvard, Vancouver, ISO, and other styles

31

Zhao, Ming-Jie, Herbert Jaeger, and Michael Thon. "Making the Error-Controlling Algorithm of Observable Operator Models Constructive." Neural Computation 21, no. 12 (December 2009): 3460–86. http://dx.doi.org/10.1162/neco.2009.10-08-878.

Full text

Abstract:

Observable operator models (OOMs) are a class of models for stochastic processes that properly subsumes the class that can be modeled by finite-dimensional hidden Markov models (HMMs). One of the main advantages of OOMs over HMMs is that they admit asymptotically correct learning algorithms. A series of learning algorithms has been developed, with increasing computational and statistical efficiency, whose recent culmination was the error-controlling (EC) algorithm developed by the first author. The EC algorithm is an iterative, asymptotically correct algorithm that yields (and minimizes) an assured upper bound on the modeling error. The run time is faster by at least one order of magnitude than EM-based HMM learning algorithms and yields significantly more accurate models than the latter. Here we present a significant improvement of the EC algorithm: the constructive error-controlling (CEC) algorithm. CEC inherits from EC the main idea of minimizing an upper bound on the modeling error but is constructive where EC needs iterations. As a consequence, we obtain further gains in learning speed without loss in modeling accuracy.

APA, Harvard, Vancouver, ISO, and other styles

32

ZAIKIN, A., J. KURTHS, P. SAPARIN, W. GOWIN, and S. PROHASKA. "MODELING BONE RESORPTION IN 2D CT AND 3D μCT IMAGES." International Journal of Bifurcation and Chaos 15, no. 09 (September 2005): 2995–3009. http://dx.doi.org/10.1142/s0218127405013836.

Full text

Abstract:

We study several algorithms to simulate bone mass loss in two-dimensional and three-dimensional computed tomography bone images. The aim is to extrapolate and predict the bone loss, to provide test objects for newly developed structural measures, and to understand the physical mechanisms behind the bone alteration. Our bone model approach differs from those already reported in the literature by two features. First, we work with original bone images, obtained by computed tomography (CT); second, we use structural measures of complexity to evaluate bone resorption and to compare it with the data provided by CT. This gives us the possibility to test algorithms of bone resorption by comparing their results with experimentally found dependencies of structural measures of complexity, as well as to show efficiency of the complexity measures in the analysis of bone models. For two-dimensional images we suggest two algorithms, a threshold algorithm and a virtual slicing algorithm. The threshold algorithm simulates bone resorption on a boundary between bone and marrow, representing an activity of osteoclasts. The virtual slicing algorithm uses a distribution of the bone material between several virtually created slices to achieve statistically correct results, when the bone-marrow transition is not clearly defined. These algorithms have been tested for original CT 10 mm thick vertebral slices and for simulated 10 mm thick slices constructed from ten 1 mm thick slices. For three-dimensional data, we suggest a variation of the threshold algorithm and apply it to bone images. The results of modeling have been compared with CT images using structural measures of complexity in two- and three-dimensions. This comparison has confirmed credibility of a virtual slicing modeling algorithm for two-dimensional data and a threshold algorithm for three-dimensional data.

APA, Harvard, Vancouver, ISO, and other styles

33

Cao, Xiaoyong, and Pu Tian. "“Dividing and Conquering” and “Caching” in Molecular Modeling." International Journal of Molecular Sciences 22, no. 9 (May 10, 2021): 5053. http://dx.doi.org/10.3390/ijms22095053.

Full text

Abstract:

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes “dividing and conquering” and/or “caching” in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but results are not transferable. Deep learning has been utilized to realize more efficient and accurate ways of “dividing and conquering” and “caching” along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science. This framework is based on a third class of algorithm that facilitates molecular modeling through partially transferable in resolution “caching” of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for “dividing and conquering” and “caching” in complex molecular systems.

APA, Harvard, Vancouver, ISO, and other styles

34

Redreev, G. V., V. D. Chervenchuk, I. V. Chervenchuk, and A. I. Zabudsky. "Interface modeling algorithms for dispatch control." IOP Conference Series: Earth and Environmental Science 624 (January 8, 2021): 012092. http://dx.doi.org/10.1088/1755-1315/624/1/012092.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Apishev, M. A. "Effective Implementations of Topic Modeling Algorithms." Programming and Computer Software 47, no. 7 (December 2021): 483–92. http://dx.doi.org/10.1134/s0361768821070021.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

O'Leary, John W., and David M. Russinoff. "Modeling Algorithms in SystemC and ACL2." Electronic Proceedings in Theoretical Computer Science 152 (June 4, 2014): 145–62. http://dx.doi.org/10.4204/eptcs.152.12.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Redreev, G. V., V. D. Chervenchuk, I. V. Chervenchuk, and A. I. Zabudsky. "Interface modeling algorithms for dispatch control." IOP Conference Series: Earth and Environmental Science 624 (January 8, 2021): 012092. http://dx.doi.org/10.1088/1755-1315/624/1/012092.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Chakraborty, M., and S. Prasad. "Multivariate ARMA modeling by scalar algorithms." IEEE Transactions on Signal Processing 41, no. 4 (April 1993): 1692–97. http://dx.doi.org/10.1109/78.212746.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Azeem, Mohammad Fazle, M. Hanmandlu, and Nesar Ahmad. "Evolutive Learning Algorithms for Fuzzy Modeling." International Journal of Smart Engineering System Design 5, no. 4 (October 2003): 205–24. http://dx.doi.org/10.1080/10255810390245546.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Apishev, Murat Azamatovich. "Effective implementations of topic modeling algorithms." Proceedings of the Institute for System Programming of the RAS 32, no. 1 (2020): 137–52. http://dx.doi.org/10.15514/ispras-2020-32(1)-8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Hanuliak, Peter. "Complex Modeling of Matrix Parallel Algorithms." American Journal of Networks and Communications 3, no. 5 (2014): 1. http://dx.doi.org/10.11648/j.ajnc.s.2014030501.11.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Hanuliak, Peter. "Complex Performance Modeling of Parallel Algorithms." American Journal of Networks and Communications 3, no. 5 (2014): 15. http://dx.doi.org/10.11648/j.ajnc.s.2014030501.12.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Pyka, M., D. Heider, S. Hauke, T. Kircher, and A. Jansen. "Dynamic causal modeling with genetic algorithms." Journal of Neuroscience Methods 194, no. 2 (January 2011): 402–6. http://dx.doi.org/10.1016/j.jneumeth.2010.11.007.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Aravkin, Aleksandr, James V. Burke, Lennart Ljung, Aurelie Lozano, and Gianluigi Pillonetto. "Generalized Kalman smoothing: Modeling and algorithms." Automatica 86 (December 2017): 63–86. http://dx.doi.org/10.1016/j.automatica.2017.08.011.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Boult, Terrance E. "Optimal algorithms: Tools for mathematical modeling." Journal of Complexity 3, no. 2 (June 1987): 183–200. http://dx.doi.org/10.1016/0885-064x(87)90026-4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Nix, Allen E., and Michael D. Vose. "Modeling genetic algorithms with Markov chains." Annals of Mathematics and Artificial Intelligence 5, no. 1 (March 1992): 79–88. http://dx.doi.org/10.1007/bf01530781.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Carroll, David L. "Chemical laser modeling with genetic algorithms." AIAA Journal 34, no. 2 (February 1996): 338–46. http://dx.doi.org/10.2514/3.13069.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Šourek, Gustav, and Petr Pošík. "Dynamic system modeling of evolutionary algorithms." ACM SIGAPP Applied Computing Review 15, no. 4 (February 17, 2016): 19–30. http://dx.doi.org/10.1145/2893706.2893708.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Cabral, Hermano A., and M. T. de Melo. "Using Genetic Algorithms for Device Modeling." IEEE Transactions on Magnetics 47, no. 5 (May 2011): 1322–25. http://dx.doi.org/10.1109/tmag.2010.2099107.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Melamed, Benjamin, and Santokh Singh. "Parallelization algorithms for modeling ARM processes." Journal of Applied Mathematics and Stochastic Analysis 13, no. 4 (January 1, 2000): 393–410. http://dx.doi.org/10.1155/s1048953300000332.

Full text

Abstract:

AutoRegressive Modular (ARM) processes are a new class of nonlinear stochastic processes, which can accurately model a large class of stochastic processes, by capturing the empirical distribution and autocorrelation function simultaneously. Given an empirical sample path, the ARM modeling procedure consists of two steps: a global search for locating the minima of a nonlinear objective function over a large parametric space, and a local optimization of optimal or near optimal models found in the first step. In particular, since the first task calls for the evaluation of the objective function at each vector of the search space, the global search is a time consuming procedure. To speed up the computations, parallelization of the global search can be effectively used by partitioning the search space among multiple processors, since the requisite communication overhead is negligible.This paper describes two space-partitioning methods, called Interleaving and Segmentation, respectively. The speedups resulting from these methods are compared for their performance in modeling real-life data.

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!