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Journal articles on the topic 'Interactive Multiple Model algoritmus'

Author: Grafiati

Published: 28 June 2021

Last updated: 8 February 2022

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1

Liu, Qiaoran, and Xun Yang. "Improved Interacting Multiple Model Particle Filter Algorithm." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 36, no. 1 (2018): 169–75. http://dx.doi.org/10.1051/jnwpu/20183610169.

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For the issue of limited filtering accuracy of interactive multiple model particle filter algorithm caused by the resampling particles don't contain the latest observation information, we made improvements on interactive multiple model particle filter algorithm in this paper based on mixed kalman particle filter algorithm. Interactive multiple model particle filter algorithm is proposed. In addition, the composed methods influence to tracking accuracy are discussed. In the new algorithm the system state estimation is generated with unscented kalman filter (UKF) first and then use the extended

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Liu, Ming Yong, Yang Li, and Xiao Jian Zhang. "A Research on the Weight of Interactive Multiple Model in Maneuvering Target Tracking." Applied Mechanics and Materials 568-570 (June 2014): 1008–11. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.1008.

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The establishment of the target model is the key of maneuvering target tracking. The previous research on interactive multiple model, which is applied on tracking extensively, focused on the design of the model set and fusion with other algorithms, while there is less study on change mechanisms of the model weight. In light of this, the impetus behind this paper is to do some analysis which based on the model weight of different trajectories, reveal the change rule. Finally, the validity of the proposed approach is demonstrated by simulation.

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Funkhouser, Thomas, Seth Teller, Carlo Séquin, and Delnaz Khorramabadi. "The UC Berkeley System for Interactive Visualization of Large Architectural Models." Presence: Teleoperators and Virtual Environments 5, no. 1 (1996): 13–44. http://dx.doi.org/10.1162/pres.1996.5.1.13.

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Realistic-looking architectural models with furniture may consist of millions of polygons and require gigabytes of data—far than today's workstations can render at interactive frame rates or store in physical memory. We have developed data structures and algorithms for identifying a small portion of a large model to load into memory and render during each frame of an interactive walkthrough. Our algorithms rely upon an efficient display database that represents a building model as a set of objects, each of which can be described at multiple levels of detail, and contains an index of spatial ce

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Tanaka, Misato, Yasunari Sasaki, Mitsunori Miki, and Tomoyuki Hiroyasu. "Crossover Method for Interactive Genetic Algorithms to Estimate Multimodal Preferences." Applied Computational Intelligence and Soft Computing 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/302573.

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We apply an interactive genetic algorithm (iGA) to generate product recommendations. iGAs search for a single optimum point based on a user’s Kansei through the interaction between the user and machine. However, especially in the domain of product recommendations, there may be numerous optimum points. Therefore, the purpose of this study is to develop a new iGA crossover method that concurrently searches for multiple optimum points for multiple user preferences. The proposed method estimates the locations of the optimum area by a clustering method and then searches for the maximum values of th

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Čertický, Martin, Michal Čertický, Peter Sinčák, Gergely Magyar, Ján Vaščák, and Filippo Cavallo. "Psychophysiological Indicators for Modeling User Experience in Interactive Digital Entertainment." Sensors 19, no. 5 (2019): 989. http://dx.doi.org/10.3390/s19050989.

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Analyses of user experience in the electronic entertainment industry currently rely on self-reporting methods, such as surveys, ratings, focus group interviews, etc. We argue that self-reporting alone carries inherent problems—mainly the misinterpretation and temporal delay during longer experiments—and therefore, should not be used as a sole metric. To tackle this problem, we propose the possibility of modeling consumer experience using psychophysiological measures and demonstrate how such models can be trained using machine learning methods. We use a machine learning approach to model user e

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Chanyaswad, Thee, Changchang Liu, and Prateek Mittal. "RON-Gauss: Enhancing Utility in Non-Interactive Private Data Release." Proceedings on Privacy Enhancing Technologies 2019, no. 1 (2019): 26–46. http://dx.doi.org/10.2478/popets-2019-0003.

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Abstract A key challenge facing the design of differential privacy in the non-interactive setting is to maintain the utility of the released data. To overcome this challenge, we utilize the Diaconis-Freedman-Meckes (DFM) effect, which states that most projections of high-dimensional data are nearly Gaussian. Hence, we propose the RON-Gauss model that leverages the novel combination of dimensionality reduction via random orthonormal (RON) projection and the Gaussian generative model for synthesizing differentially-private data. We analyze how RON-Gauss benefits from the DFM effect, and present

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Okkan, Umut, and Umut Kirdemir. "Towards a hybrid algorithm for the robust calibration of rainfall–runoff models." Journal of Hydroinformatics 22, no. 4 (2020): 876–99. http://dx.doi.org/10.2166/hydro.2020.016.

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Abstract In this study, the hybrid particle swarm optimization (HPSO) algorithm was proposed and practised for the calibration of two conceptual rainfall–runoff models (dynamic water balance model and abcde). The performance of the developed method was compared with those of several metaheuristics. The models were calibrated for three sub-basins, and multiple performance criteria were taken into consideration in comparison. The results indicated that HPSO was derived significantly better and more consistent results than other algorithms with respect to hydrological model errors and convergence

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SHINDE, AMIT, MOEED HAGHNEVIS, MARCO A. JANSSEN, GEORGE C. RUNGER, and MANI JANAKIRAM. "SCENARIO ANALYSIS OF TECHNOLOGY PRODUCTS WITH AN AGENT-BASED SIMULATION AND DATA MINING FRAMEWORK." International Journal of Innovation and Technology Management 10, no. 05 (2013): 1340019. http://dx.doi.org/10.1142/s0219877013400191.

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A framework is presented to simulate and analyze the effect of multiple business scenarios on the adoption behavior of a group of technology products. Diffusion is viewed as an emergent phenomenon that results from the interaction of consumers. An agent-based model is used in which potential adopters of technology product are allowed to be influenced by their local interactions within the social network. Along with social influence, the effect of product features is important and we ascribe feature sensing attributes to the consumer agents along with sensitivities to social influence. The mode

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Tavana, Madjid, Dawn A. Trevisani, and Jerry L. Dussault. "The Stability Model." International Journal of Information Technology Project Management 4, no. 2 (2013): 18–34. http://dx.doi.org/10.4018/jitpm.2013040102.

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The increasing complexity and tight coupling between people and technology in military Command and Control (C2) systems has led to greater vulnerability due to system failure. Although system vulnerabilities cannot be completely eliminated, the accidental or anticipated failures have to be thoroughly understood and guarded. Traditionally, the failure in C2 systems has been studied with resiliency and the concept of self-healing systems represented with reactive models or robustness and the concept of self-protecting systems represented with proactive models. The authors propose the stability m

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Butterworth, Erik, Bartholomew E. Jardine, Gary M. Raymond, Maxwell L. Neal, and James B. Bassingthwaighte. "JSim, an open-source modeling system for data analysis." F1000Research 2 (December 30, 2013): 288. http://dx.doi.org/10.12688/f1000research.2-288.v1.

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JSim is a simulation system for developing models, designing experiments, and evaluating hypotheses on physiological and pharmacological systems through the testing of model solutions against data. It is designed for interactive, iterative manipulation of the model code, handling of multiple data sets and parameter sets, and for making comparisons among different models running simultaneously or separately. Interactive use is supported by a large collection of graphical user interfaces for model writing and compilation diagnostics, defining input functions, model runs, selection of algorithms

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Butterworth, Erik, Bartholomew E. Jardine, Gary M. Raymond, Maxwell L. Neal, and James B. Bassingthwaighte. "JSim, an open-source modeling system for data analysis." F1000Research 2 (May 12, 2014): 288. http://dx.doi.org/10.12688/f1000research.2-288.v2.

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JSim is a simulation system for developing models, designing experiments, and evaluating hypotheses on physiological and pharmacological systems through the testing of model solutions against data. It is designed for interactive, iterative manipulation of the model code, handling of multiple data sets and parameter sets, and for making comparisons among different models running simultaneously or separately. Interactive use is supported by a large collection of graphical user interfaces for model writing and compilation diagnostics, defining input functions, model runs, selection of algorithms

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Butterworth, Erik, Bartholomew E. Jardine, Gary M. Raymond, Maxwell L. Neal, and James B. Bassingthwaighte. "JSim, an open-source modeling system for data analysis." F1000Research 2 (July 1, 2014): 288. http://dx.doi.org/10.12688/f1000research.2-288.v3.

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JSim is a simulation system for developing models, designing experiments, and evaluating hypotheses on physiological and pharmacological systems through the testing of model solutions against data. It is designed for interactive, iterative manipulation of the model code, handling of multiple data sets and parameter sets, and for making comparisons among different models running simultaneously or separately. Interactive use is supported by a large collection of graphical user interfaces for model writing and compilation diagnostics, defining input functions, model runs, selection of algorithms

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Barlowe, Scott, Heather B. Coan, and Robert T. Youker. "SubVis: an interactive R package for exploring the effects of multiple substitution matrices on pairwise sequence alignment." PeerJ 5 (June 27, 2017): e3492. http://dx.doi.org/10.7717/peerj.3492.

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Understanding how proteins mutate is critical to solving a host of biological problems. Mutations occur when an amino acid is substituted for another in a protein sequence. The set of likelihoods for amino acid substitutions is stored in a matrix and input to alignment algorithms. The quality of the resulting alignment is used to assess the similarity of two or more sequences and can vary according to assumptions modeled by the substitution matrix. Substitution strategies with minor parameter variations are often grouped together in families. For example, the BLOSUM and PAM matrix families are

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Sakawa, Masatoshi, and Kosuke Kato. "An Interactive Fuzzy Satisficing Method for Multiobjective Nonlinear Integer Programming Problems with Block-Angular Structures through Genetic Algorithms with Decomposition Procedures." Advances in Operations Research 2009 (2009): 1–17. http://dx.doi.org/10.1155/2009/372548.

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We focus on multiobjective nonlinear integer programming problems with block-angular structures which are often seen as a mathematical model of large-scale discrete systems optimization. By considering the vague nature of the decision maker's judgments, fuzzy goals of the decision maker are introduced, and the problem is interpreted as maximizing an overall degree of satisfaction with the multiple fuzzy goals. For deriving a satisficing solution for the decision maker, we develop an interactive fuzzy satisficing method. Realizing the block-angular structures that can be exploited in solving pr

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Vakil, Vahideh, and Wade Trappe. "Drug Combinations: Mathematical Modeling and Networking Methods." Pharmaceutics 11, no. 5 (2019): 208. http://dx.doi.org/10.3390/pharmaceutics11050208.

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Treatments consisting of mixtures of pharmacological agents have been shown to have superior effects to treatments involving single compounds. Given the vast amount of possible combinations involving multiple drugs and the restrictions in time and resources required to test all such combinations in vitro, mathematical methods are essential to model the interactive behavior of the drug mixture and the target, ultimately allowing one to better predict the outcome of the combination. In this review, we investigate various mathematical methods that model combination therapies. This survey includes

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Jeong, G., N. Freitas, Y. Cho, and C. Han. "[AI-Machine Learning] Optimized Sensorless Human Pose Estimation for a Kpop Dance Application." Volume 5 - 2020, Issue 8 - August 5, no. 8 (2020): 893–96. http://dx.doi.org/10.38124/ijisrt20aug003.

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There has been a great effort to use technology to make exercise more interactive, measurable and gamified. However, in order to optimize the detection accuracy, these efforts have always translated themselves into motion detection with multiple sensors including purpose specific hardware, which results in extra expenses on both the content production and consumption and induces limitations on the final mobility of the user. In this paper we aim to improve the accuracy, learning speed and detail range of Posenet’s AI sensorless human pose detection by using an artificial neural network to opti

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17

Qin, Li, Hongyu Wang, Yazhou Yuan, and Shufan Qin. "Multi-Sensor Perception Strategy to Enhance Autonomy of Robotic Operation for Uncertain Peg-in-Hole Task." Sensors 21, no. 11 (2021): 3818. http://dx.doi.org/10.3390/s21113818.

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The peg-in-hole task with object feature uncertain is a typical case of robotic operation in the real-world unstructured environment. It is nontrivial to realize object perception and operational decisions autonomously, under the usual visual occlusion and real-time constraints of such tasks. In this paper, a Bayesian networks-based strategy is presented in order to seamlessly combine multiple heterogeneous senses data like humans. In the proposed strategy, an interactive exploration method implemented by hybrid Monte Carlo sampling algorithms and particle filtering is designed to identify the

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18

Liu, Hongqiang, Zhongliang Zhou, and Lei Yu. "Maneuvering Acceleration Estimation Algorithm Using Doppler Radar Measurement." Mathematical Problems in Engineering 2018 (June 4, 2018): 1–13. http://dx.doi.org/10.1155/2018/4984186.

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An algorithm to estimate the tangential and normal accelerations directly using the Doppler radar measurement in an online closed loop form is proposed. Specific works are as follows: first, the tangential acceleration and normal acceleration are taken as the state variables to establish a linear state transition equation; secondly, the decorrelation unbiased conversion measurement Kalman filter (DUCMKF) algorithm is proposed to deal with the strongly nonlinear measurement equation; thirdly, the geometric relationship between the range rate and the velocity direction angle is used to obtain tw

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Yang, Xiaohui, Jiating Long, Peiyun Liu, Xiaolong Zhang, and Xiaoping Liu. "Optimal Scheduling of Microgrid with Distributed Power Based on Water Cycle Algorithm." Energies 11, no. 9 (2018): 2381. http://dx.doi.org/10.3390/en11092381.

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Microgrid, taking advantage of distributed power generation technology, plays an important role in maximizing the utilization of renewable energy. Based on the problems of the energy crisis, environmental contamination and the high operating cost of the microgrid, the microgrid model can effectively ease energy pressure. We can dispatch the output of each part in the microgrid to obtain the optimal economy. Since many traditional optimization algorithms have limitations of local optimization, multiple iterations, and slow convergence speed, this paper proposes a method that applies the Water C

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20

Zhao, Jin Xiao, Jian Qiu Zhang, and Dong Ming Zhou. "Polynomial Model Set and its Interacting Multiple Model Algorithms." Advanced Materials Research 562-564 (August 2012): 2038–44. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.2038.

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From the maneuvering target orbit on the geometrical properties, according to different motion modes track corresponding to different order number polynomial curve, using the least squares fitting structure, this paper gives out a group of various motion modes matching the mathematical model—polynomial model set (PMS), and gives distinct mathematical process. PMS covers all the motion modes theoretically, easy to choose according to the practical situation and expand, especially suitable for single model can not accurately describe the complex sports scene. The model need not consider sampling

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Yan, Shuyuan, Bolin Ding, Wei Guo, et al. "FlashP." Proceedings of the VLDB Endowment 14, no. 5 (2021): 721–29. http://dx.doi.org/10.14778/3446095.3446096.

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Interactive response time is important in analytical pipelines for users to explore a sufficient number of possibilities and make informed business decisions. We consider a forecasting pipeline with large volumes of high-dimensional time series data. Real-time forecasting can be conducted in two steps. First, we specify the part of data to be focused on and the measure to be predicted by slicing, dicing, and aggregating the data. Second, a forecasting model is trained on the aggregated results to predict the trend of the specified measure. While there are a number of forecasting models availab

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Semerdjiev, Emil, Ludmila Mihaylova, Tzvetan Semerdjiev, and Violeta Bogdanova. "Interacting Multiple Model Algorithms for Manoeuvring Ship Tracking Based On New Ship Models." Information & Security: An International Journal 2 (1999): 122–37. http://dx.doi.org/10.11610/isij.0211.

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23

Shen, Ye, Stephen Vosti, Beatrice Rogers, and Patrick Webb. "Integrating Cost-Effectiveness into Nutrition Programming Decisions of Specialized Nutritious Foods: An Evidence-Informed Interactive Tool." Current Developments in Nutrition 4, Supplement_2 (2020): 906. http://dx.doi.org/10.1093/cdn/nzaa053_111.

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Abstract Objectives An interactive Food Assistance Cost-Effectiveness Tool (FACET) was created to support funders and implementing partners of selected nutrition programs involving specialized nutritious foods (SNF) to factor cost-effectiveness into programming decisions in development and humanitarian contexts. Methods Built with the Shiny package in R, the FACET interface guides users through the process of integrating user-provided data and scientific evidence into program decision-making under a cost-effectiveness framework. Users create a scenario by inputting choices or values for progra

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Horton, Pascal. "AtmoSwing: Analog Technique Model for Statistical Weather forecastING and downscalING (v2.1.0)." Geoscientific Model Development 12, no. 7 (2019): 2915–40. http://dx.doi.org/10.5194/gmd-12-2915-2019.

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Abstract. Analog methods (AMs) use synoptic-scale predictors to search in the past for similar days to a target day in order to infer the predictand of interest, such as daily precipitation. They can rely on outputs of numerical weather prediction (NWP) models in the context of operational forecasting or outputs of climate models in the context of climate impact studies. AMs require low computing capacity and have demonstrated useful potential for application in several contexts. AtmoSwing is open-source software written in C++ that implements AMs in a flexible way so that different variants c

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Zhao, Bi, Akila Katuwawala, Christopher J. Oldfield, et al. "DescribePROT: database of amino acid-level protein structure and function predictions." Nucleic Acids Research 49, no. D1 (2020): D298—D308. http://dx.doi.org/10.1093/nar/gkaa931.

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Abstract We present DescribePROT, the database of predicted amino acid-level descriptors of structure and function of proteins. DescribePROT delivers a comprehensive collection of 13 complementary descriptors predicted using 10 popular and accurate algorithms for 83 complete proteomes that cover key model organisms. The current version includes 7.8 billion predictions for close to 600 million amino acids in 1.4 million proteins. The descriptors encompass sequence conservation, position specific scoring matrix, secondary structure, solvent accessibility, intrinsic disorder, disordered linkers,

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Yuan, Xianghui, Feng Lian, and Chongzhao Han. "Models and Algorithms for Tracking Target with Coordinated Turn Motion." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/649276.

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Tracking target with coordinated turn (CT) motion is highly dependent on the models and algorithms. First, the widely used models are compared in this paper—coordinated turn (CT) model with known turn rate, augmented coordinated turn (ACT) model with Cartesian velocity, ACT model with polar velocity, CT model using a kinematic constraint, and maneuver centered circular motion model. Then, in the single model tracking framework, the tracking algorithms for the last four models are compared and the suggestions on the choice of models for different practical target tracking problems are given. Fi

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Zhou, Weidong, and Mengmeng Liu. "Robust interacting multiple model algorithms based on multi-sensor fusion criteria." International Journal of Systems Science 47, no. 1 (2015): 92–106. http://dx.doi.org/10.1080/00207721.2015.1029566.

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Wang, Xiao Yan, Gui Xiang Shen, Ying Zhi Zhang, and Shu Guang Sun. "An Analytical Model of Interactive Coefficients of Multiple Systems." Advanced Materials Research 1030-1032 (September 2014): 1292–95. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.1292.

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Dependent failures of machines may take many forms. Interactive failure is one type of the dependent failures happening among multiple subsystems. The interactive coefficient is represented by the degree of interaction between two subsystems, but it cannot be estimated in intricate interactive relationship among multiple subsystems by now. In order to solve the problem, the failure chains of the interactive failure are classified into five types in this paper and all the elements in it are defined. Then the interactive coefficient models are developed for all failure chains according to the re

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Li, Zhen-Xing, Yun Wang, Jin-Mang Liu, Ni Peng, and Lin-Hai Gan. "Variable-structure interacting multiple-model estimation for group targets tracking with random matrices." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, no. 7 (2017): 1201–11. http://dx.doi.org/10.1177/0954410016688123.

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In order to improve the estimation performance of interacting multiple model tracking algorithm for group targets, the expected-mode augmentation variable-structure interacting multiple model (EMA-VSIMM) and the best model augmentation variable-structure interacting multiple model (BMA-VSIMM) tracking algorithms are presented in this paper. First, by using the EMA method, a more proper expected-mode set has been chosen from the basic model set of group targets, which can make the selected tracking models better match up to the true mode. The BMA algorithm uses a fixed parameter model of differ

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Jovandic, Igor, Zeljko Djurovic, and Branko Kovacevic. "Adaptive filtering algorithms in target tracking applications." Facta universitatis - series: Electronics and Energetics 16, no. 3 (2003): 317–26. http://dx.doi.org/10.2298/fuee0303317j.

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Comparison of several target tracking algorithms is presented. Namely discrete noise level adjustment (DNLA), variable state dimension (VSD) and interacting multiple model (IMM) algorithms are discussed. Target trajectory, target models, filtering algorithms and simulation results are given. The cumulative estimation error criterion is used in order to compare the algorithms.

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Liu, Hong Jiang. "Adaptive Interacting Multiple Model Unscented Particle Filter Tracking Algorithm." Applied Mechanics and Materials 190-191 (July 2012): 906–10. http://dx.doi.org/10.4028/www.scientific.net/amm.190-191.906.

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In order to study the tracking problem of maneuvering image sequence target in complex environment with multi-sensor array, the adaptive interacting multiple model unscented particle filter algorithm based on measured residual is proposed. The motion array tracking system dynamic model is established, and initialized probability density function also is defined based on unscented transformation, after that, the measured covariance and state covariance are online adjusted by measured residual and adaptive factor, then the self-adapting capability of filter gain and the real-time capability of p

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Tang, Fuhui, Xiankai Lu, Xiaoyu Zhang, Shiqiang Hu, and Huanlong Zhang. "Deep feature tracking based on interactive multiple model." Neurocomputing 333 (March 2019): 29–40. http://dx.doi.org/10.1016/j.neucom.2018.12.035.

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Wang, Zhenshu, Na Ji, Yangyang Ma, Zhanjie Liu, and Yu Wang. "Model selection mechanism of Interactive Multiple Load Modeling." International Journal of Electrical Power & Energy Systems 103 (December 2018): 58–66. http://dx.doi.org/10.1016/j.ijepes.2018.05.027.

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Ding, Zhen. "Static/dynamic distributed interacting multiple model fusion algorithms for multiplatform multisensor tracking." Optical Engineering 36, no. 3 (1997): 708. http://dx.doi.org/10.1117/1.601268.

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Fu, X., Y. Jia, F. Yu, and J. Du. "New interacting multiple model algorithms for the tracking of the manoeuvring target." IET Control Theory & Applications 4, no. 10 (2010): 2184–94. http://dx.doi.org/10.1049/iet-cta.2009.0583.

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Xue, Li, Yulan Han, and Chunning Na. "Robust Interacting Multiple Model Unscented Particle Filter for Navigation." Mathematical Problems in Engineering 2020 (November 10, 2020): 1–10. http://dx.doi.org/10.1155/2020/8871358.

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In order to solve the problems of particle degradation and difficulty in selecting importance density function in particle filter algorithm, a robust interacting multiple model unscented particle filter algorithm is presented, which is based on the advantages of interacting multiple model and particle filter algorithms. This algorithm can use the unscented transformation to get the particles that contain the latest measurement information of each model and calculate the robust equivalent weight function. This robust factor is designed to adjust the estimation and variance, and the important di

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Lim, Jaechan, Hun-Seok Kim, and Hyung-Min Park. "Interactive-Multiple-Model Algorithm Based on Minimax Particle Filtering." IEEE Signal Processing Letters 27 (2020): 36–40. http://dx.doi.org/10.1109/lsp.2019.2954000.

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Zhu, Meiyu, Guanyu Chen, and Weicun Zhang. "Maneuvering target tracking with improved interactive multiple model algorithm." Proceedings of International Conference on Artificial Life and Robotics 26 (January 21, 2021): 373–76. http://dx.doi.org/10.5954/icarob.2021.os6-5.

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Koller, Tom L., and Udo Frese. "The Interacting Multiple Model Filter and Smoother on Boxplus-Manifolds." Sensors 21, no. 12 (2021): 4164. http://dx.doi.org/10.3390/s21124164.

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Hybrid systems are subject to multiple dynamic models, or so-called modes. To estimate the state, the sequence of modes has to be estimated, which results in an exponential growth of possible sequences. The most prominent solution to handle this is the interacting multiple model filter, which can be extended to smoothing. In this paper, we derive a novel generalization of the interacting multiple filter and smoother to manifold state spaces, e.g., quaternions, based on the boxplus-method. As part thereof, we propose a linear approximation to the mixing of Gaussians and a Rauch–Tung–Striebel sm

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Zhou, Wei dong, Jia nan Cai, Long Sun, and Chen Shen. "An Improved Interacting Multiple Model Algorithm Used in Aircraft Tracking." Mathematical Problems in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/813654.

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There are some problems in traditional interacting multiple model algorithms (IMM) when used in target tracking systems. For instance, the mode transition matrix is inaccurate and cannot be determined when the sojourn times are not known. To solve these problems, an optimal mode transition matrix IMM (OMTM-IMM) algorithm is proposed in this paper. The linear minimum variance theory is used to calculate the mode transition matrix which depends on the continuous system state rather than the sojourn times in this algorithm. Moreover, the correlation of the subfilter is considered; hence the covar

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Cheng, Long, Sihang Huang, Mingkun Xue, and Yangyang Bi. "A Robust Localization Algorithm Based on NLOS Identification and Classification Filtering for Wireless Sensor Network." Sensors 20, no. 22 (2020): 6634. http://dx.doi.org/10.3390/s20226634.

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With the rapid development of information and communication technology, the wireless sensor network (WSN) has shown broad application prospects in a growing number of fields. The non-line-of-sight (NLOS) problem is the main challenge to WSN localization, which seriously reduces the positioning accuracy. In this paper, a robust localization algorithm based on NLOS identification and classification filtering for WSN is proposed to solve this problem. It is difficult to use a single filter to filter out NLOS noise in all cases since NLOS cases are extremely complicated in real scenarios. Therefor

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Liu, Ya Lei, and Xiao Hui Gu. "Adaptive Interacting Multiple Model Unscented Particle Filter for Dynamic Acoustic Array." Applied Mechanics and Materials 300-301 (February 2013): 407–13. http://dx.doi.org/10.4028/www.scientific.net/amm.300-301.407.

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Abstract. In order to improve the tracking accuracy of 3D dynamic acoustic array to 2D maneuvering target in colored noise environment, the adaptive interacting multiple model unscented particle filter algorithm based on measured residual is proposed. The 3D motion acoustic array tracking system dynamic model is established, and initialized probability density function also is defined based on unscented transformation, after that, the measured covariance and state covariance are online adjusted by measured residual and adaptive factor, then the self-adapting capability of filter gain and the r

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Shaikh, Bilal, Gnaneswara Marupilla, Mike Wilson, Michael L. Blinov, Ion I. Moraru, and Jonathan R. Karr. "RunBioSimulations: an extensible web application that simulates a wide range of computational modeling frameworks, algorithms, and formats." Nucleic Acids Research 49, W1 (2021): W597—W602. http://dx.doi.org/10.1093/nar/gkab411.

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Abstract Comprehensive, predictive computational models have significant potential for science, bioengineering, and medicine. One promising way to achieve more predictive models is to combine submodels of multiple subsystems. To capture the multiple scales of biology, these submodels will likely require multiple modeling frameworks and simulation algorithms. Several community resources are already available for working with many of these frameworks and algorithms. However, the variety and sheer number of these resources make it challenging to find and use appropriate tools for each model, espe

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Yun, Joongsup, and Chang-Kyung Ryoo. "Missile Guidance Law Estimation Using Modified Interactive Multiple Model Filter." Journal of Guidance, Control, and Dynamics 37, no. 2 (2014): 484–96. http://dx.doi.org/10.2514/1.61327.

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ATANASOV, Deyan. "TRACKING MANEUVERING TARGET WITH KALMAN FILTER AND INTERACTIVE MULTIPLE MODEL." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 21, no. 1 (2019): 88–97. http://dx.doi.org/10.19062/2247-3173.2019.21.13.

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Yao, Yao, Yuanyuan Li, Xi Xiong, Yue Wu, Honggang Lin, and Shenggen Ju. "An interactive propagation model of multiple information in complex networks." Physica A: Statistical Mechanics and its Applications 537 (January 2020): 122764. http://dx.doi.org/10.1016/j.physa.2019.122764.

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Lotfi, Vahid, Theodor J. Stewart, and Stanley Zionts. "An aspiration-level interactive model for multiple criteria decision making." Computers & Operations Research 19, no. 7 (1992): 671–81. http://dx.doi.org/10.1016/0305-0548(92)90036-5.

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Vasuhi, S., and V. Vaidehi. "Target tracking using Interactive Multiple Model for Wireless Sensor Network." Information Fusion 27 (January 2016): 41–53. http://dx.doi.org/10.1016/j.inffus.2015.05.004.

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Bi, Suzhi, and Xiao Yi Ren. "MANEUVERING TARGET DOPPLER-BEARING TRACKING WITH SIGNAL TIME DELAY USING INTERACTING MULTIPLE MODEL ALGORITHMS." Progress In Electromagnetics Research 87 (2008): 15–41. http://dx.doi.org/10.2528/pier08091501.

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Held, Pascal, Alexander Dockhorn, and Rudolf Kruse. "On Merging and Dividing Social Graphs." Journal of Artificial Intelligence and Soft Computing Research 5, no. 1 (2015): 23–49. http://dx.doi.org/10.1515/jaiscr-2015-0017.

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Abstract Modeling social interaction can be based on graphs. However most models lack the flexibility of including larger changes over time. The Barabási-Albert-model is a generative model which already offers mechanisms for adding nodes. We will extent this by presenting four methods for merging and five for dividing graphs based on the Barabási- Albert-model. Our algorithms were motivated by different real world scenarios and focus on preserving graph properties derived from these scenarios. With little alterations in the parameter estimation those algorithms can be used for other graph mode

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