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About 10,000 papers for “modeling algorithm”

Parallel Algorithm for the Chameleon Clustering Algorithm using Dynamic Modeling

Rajnish Dashora, Harsh P. Bajaj, Akshat Dube et al. · International Journal of Computer Applications · 2013

With the increasing size of data-sets in application areas like bio-medical, hospitals, information systems, scientific data processing and predictions, finance analytics, communications, retail and marketing, it is becoming increasingly important to execute data mining tasks in parallel. At the same time, technological advancements have made shared memoryparallel computation machines commonly available to various organizations and individuals. This paper analyzes a hierarchical clustering algorithm named chameleon clustering which is based on dynamic modeling and we propose a parallel algorithm for the same. The algorithm utilizes the concept of parallel processors available and hence reduces the time to generate final clusters.

Cited by 4Open access

Research on Modeling Uncertainty of Load Modeling based on IMM Algorithm

Zhongqiang Li, Zhenshu Wang, Yongzhi Yan et al. · 2020 5th International Conference on Power and Renewable Energy (ICPRE) · 2020

With the increasing integration of clean and renewable energy, it is imperative to understand the load characteristics of power system. Accurate load model is the basis of power system security and stability analysis. An improper load model will makes the calculation results inconsistent with the actual situation. Time-varying and randomness of load characteristics are the difficulties of load modeling, and modeling uncertainty will affect the accuracy of load modeling. In order to solve this problem, modeling uncertainty compensation mechanism is proposed in this paper. By introducing modeling error compensation parameter, the weights of the system model and measurement model are adjusted in real-time to reduce the influence of modeling error. It improves the accuracy of interacting multiple load modeling. The effectiveness of the proposed method is validated by simulation results.

Cited by 1

Generalized Pattern Search Algorithm for Crustal Modeling

M. T. Dugda, Farzad Moazzami · Vide Leaf, Hyderabad eBooks · 2023

In computational seismology, receiver functions represent the impulse response for the earth structure beneath a seismic station and, in general, these are functionals that show several seismic phases in the time-domain related to discontinuities within the crust and the upper mantle.This paper introduces a new technique called generalized pattern search (GPS) for inverting receiver functions to obtain the depth of the crust-mantle discontinuity, i.e., the crustal thickness H, and the ratio of crustal P-wave velocity Vp to S-wave velocity Vs.In particular, the GPS technique, which is a direct search method, does not need derivative or directional vector information.Moreover, the technique allows simultaneous determination of the weights needed for the converted and reverberated phases.Compared to previously introduced variable weights approaches for inverting H-κ stacking of receiver functions, with κ = Vp/Vs, the GPS technique has some advantages in terms of saving computational time and also suitability for simultaneous determination of crustal parameters and associated weights.Finally, the technique is tested using seismic data from the East Africa Rift System and it provides results that are consistent with previously published studies.

Cited by 1Open access

A Robust Boosting Algorithm for Chemical Modeling

Ville Satopää, Richard D. De Veaux · Current Analytical Chemistry · 2012

Bagging and boosting have become increasingly important ensemble methods for combining models in the data mining and machine learning literature. We review the basic ideas of these methods, propose a new robust boosting algorithm based on a non-convex loss function and compare the performance of these methods to both simulated and real data sets with and without contamination.

Cited by 0

Background Modeling Algorithm Based on Transitions Intensities

Siham Aqel, My Abdelouahed Sabri, Abdellah Aarab · International Review on Computers and Software (IRECOS) · 2015

Moving objects detection in a scene from a video sequence is a fundamental and crucial problem in many vision systems such as video surveillance or the traffic monitoring. Background modeling is often used to detect moving objects which assumes that the moving objects take less time in the scene with respect to the background. Indeed, this assumption cannot be valid in case of a scene with fast moving objects. To overcome this problem, in this paper we propose a novel background modeling approach based on transitions intensities. In other words, we will focus on intensity changes (transitions) of pixels during a scene instead of using duration information that a pixel pass in a state without any notable change in its intensity. The normalized RGB color is used to describe the appearance under change lighting conditions, and transition intensity is introduced to capture the dynamicity of objects over time. Experimental results on different video sequences have been presented to approve the effectiveness of the proposed algorithm.

Cited by 13

Fuzzy systems modeling with participatory search algorithm

Yi Ling Liu, Fernando Gomide · 2017

Participatory search is a population-based algorithm derived from the participatory learning paradigm. The algorithm accounts for the fact that the compatibility between individuals of the current population and the combination of compatibles, help to improve the value of an objective function during the search for an optimum. This paper focuses on the use of participatory search as a tool to develop fuzzy linguistic rule-based models. The performance of the models produced by participatory search algorithm is compared with a state of a start of the art genetic fuzzy system approach. Experimental results suggest that the participatory search algorithm with arithmetic-like recombination performs best.

Cited by 0

Reduced order modeling using genetic-fuzzy algorithm

Ahmad T. Abdulsadda, Kameran Iqbal · 2009

Many high-order systems have a large state space. Such systems need to additional computation time for complex calculation to find the output response. Traditionally, iteration methods have been applied to solve this problem. In this paper advantages of stability equation method derived by Parmer, [1], and the error minimization technique used in genetic-fuzzy algorithm have been combined to propose a new method for order reduction of linear dynamic systems described via state-space models. Genetic part has been used in this formulation to find the optimal solution(s) to minimize the objective function ¿J¿ that depends on the error term between the original output and the desired or reduced output. Fuzzy sets have been used to determine the step size action (point crossover or multiple crossover) depending upon fuzzy rules based on the current and previous error terms. An example of reduced order modeling from power systems is presented to illustrate the algorithm.

Cited by 4

Algorithm Development for Computational Modeling and Simulation

Nordina Syamira Mahamad Shabudin, Ahmad Naqib Shuid · BENTHAM SCIENCE PUBLISHERS eBooks · 2024

The super-fast automated next-generation sequencing (NGS) technology allows parallel sequencing of millions of genomics molecules with higher accuracy at low cost and less time consumption. However, the three-dimensional structure needs to be determined for experimental purposes, and solving the three-dimensional structure of a biomolecule via the alternative experimental approaches requires special skills and equipment, which is time-consuming, labor demanding and expensive. This situation resulted in the widening of the space between solved biological molecules and known sequences. Recently, bioinformaticians and computer scientists have developed computer-based algorithms and protocols to solve these issues. The developed computational approaches and algorithms allow researchers to 1) perform prediction and refinement of models close to their native molecule structure based on the data from other molecules possessing similar homology, 2) predict potential interaction and possible reactions between two biomolecules and 3) gain meaningful insight when it is impractical to be obtained via theoretical or experimental analysis. The development of these computational algorithms allows scientists to discover, predict and study important molecules at a faster pace. This chapter will introduce readers to the basic computational algorithms used to develop advanced bioinformatic protocols and tools.

Cited by 0

A practical algorithm for topic modeling with . . .

Sanjeev Arora, Rong Ge, Yoni Halpern, David Mimno et al. · 2013

Topic models provide a useful method for dimensionality reduction and exploratory data analysis in large text corpora. Most approaches to topic model learning have been based on a maximum likelihood objective. Efficient algorithms exist that attempt to approximate this objective, but they have no provable guarantees. Recently, algorithms have been introduced that provide provable bounds, but these algorithms are not practical because they are inefficient and not robust to violations of model assumptions. In this paper we present an algorithm for learning topic models that is both provable and practical. The algorithm produces results comparable to the best MCMC implementations while running orders of magnitude faster.

Cited by 0

Regression modeling based on improved genetic algorithm

Shi Minghua, Xiao Qingxian, Zhou Benda et al. · SHILAP Revista de lepidopterología · 2017

Regression model is a well-established method in data analysis with applications in various fields. The selection of independent variables and mathematically transformed in a regression model is often a challenging problem. Recently, some scholars have used evolutionary computation to solve this problem, but the result is not effective as we desired. The crossover operation in GA is redesigned by using Latin hypercube sampling, then combining two commonly used statistical criteria (AIC, BIC) we are presenting an improved genetic algorithm based for solving statistical model selection problem. The proposed algorithm can overcome strong path-dependence and rely on experience of classical approaches. Comparison of simulation results in solving statistical model selection problem with this improved GA, traditional genetic algorithm and classical algorithm for model selection show that the new GA has superiority in solution of quality, convergence rate and other various indices.

Cited by 0Open access

LCD Motion Blur: Modeling, Analysis, and Algorithm

Stanley H. Chan, Truong Q. Nguyen · IEEE Transactions on Image Processing · 2011

Liquid crystal display (LCD) devices are well known for their slow responses due to the physical limitations of liquid crystals. Therefore, fast moving objects in a scene are often perceived as blurred. This effect is known as the LCD motion blur. In order to reduce LCD motion blur, an accurate LCD model and an efficient deblurring algorithm are needed. However, existing LCD motion blur models are insufficient to reflect the limitation of human-eye-tracking system. Also, the spatiotemporal equivalence in LCD motion blur models has not been proven directly in the discrete 2-D spatial domain, although it is widely used. There are three main contributions of this paper: modeling, analysis, and algorithm. First, a comprehensive LCD motion blur model is presented, in which human-eye-tracking limits are taken into consideration. Second, a complete analysis of spatiotemporal equivalence is provided and verified using real video sequences. Third, an LCD motion blur reduction algorithm is proposed. The proposed algorithm solves an l(1)-norm regularized least-squares minimization problem using a subgradient projection method. Numerical results show that the proposed algorithm gives higher peak SNR, lower temporal error, and lower spatial error than motion-compensated inverse filtering and Lucy-Richardson deconvolution algorithm, which are two state-of-the-art LCD deblurring algorithms.

Cited by 29

Algorithm for tree growth modeling and visualization

L.V. Shchegoleva, D.V. Gudach, A.V. Kabonen · FORESTRY BULLETIN · 2022

The developed algorithm for modeling the growth of a tree using the example of European spruce (Picea abies) for three-dimensional visualization of plant development is presented. A special structure of classes is proposed that form the internal structure of a tree by a set of interconnected shoots that grow from buds. They store the numerical characteristics of the structure (age, trunk diameter, shoots length and the volume of tree photosynthetic biomass) and the spatial coordinates of structural elements on the parent object (last year’s shoot). The algorithm for modeling the growth of a spruce tree includes the generation of random values for the characteristics of shoots and buds. The proposed algorithm makes it possible to realize the structural diversity of branching processes and the stochastic nature of development under the conditions of tree growth in the Republic of Karelia.

Cited by 0Open access

Adaptive threshold based codebook background modeling algorithm

W.S. Li, Yu Cao · WIT transactions on information and communication technologies · 2014

Welcome to the WIT Press eLibrary - the home of the Transactions of the Wessex Institute collection, providing on-line access to papers presented at the Institute's prestigious international conferences and from its State-of-the-Art in Science & Engineering publications.

Cited by 0

3D Face Modeling Based on SFM Algorithm

Nan Zheng · 2005

This paper proposes a whole scheme to construct textured 3D face models from two views with a few user interactions. As the human face contains many low texture and homogeneous areas, some algorithms such as corner matching are unstable and may fail sometimes. This paper uses the face definition parameters and the symmetry of human face as prior knowledge to find reliable correspondences between two pictures, while most SFM algorithms use the generic model as a modulator in the post processing steps. According to the correspondences, a multistage SFM approach is used to reconstruct the structure. Then the authors use the RBFCS algorithm to interpolate more 3D points according to the scattered feature points. Multistage image mosaic technique is used to get the texture. A user with an ordinary camera can use the algorithm to generate his realistic face model in a personal computer.

Cited by 5