Search Results - constraint-based algorithm

BayesIan network constraint-based structure learning algorithms: Parallel and optimised implementations in the bnlearn R package by Scutari, Marco

“… function to maximize. This is not true for approaches based on conditional independence tests, called constraint-based learning algorithms…”
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A novel constraint‐based genetic algorithm solution for SHE technique in modified PUC‐5 inverter by Lodi, Kaif Ahmed, Azeem, Abdul, Sarwar, Adil, Tariq, Mohd

“… (GA). The novel constraints‐based GA algorithm is applied in this work, which eliminates the third and its higher orders and fifth harmonic in the output voltage waveform…”
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Active Informative Pairwise Constraint Formulation Algorithm for Constraint-Based Clustering by Zhong, Guoxiang, Deng, Xiuqin, Xu, Shengbing

“… In this paper, we propose a novel formulation algorithm to generate more informative pairwise constraints from limited queries for the constraint-based clustering…”
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A constraint-based algorithm for causal discovery with cycles, latent variables and selection bias by Strobl, Eric V.

“… No constraint-based causal discovery algorithm can currently handle cycles, latent variables and selection bias (CLS) simultaneously…”
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Gradient entropy metric and p-Laplace diffusion constraint-based algorithm for noisy multispectral image fusion by Zhao, Wenda, Xu, Zhijun, Zhao, Jian

“… In this paper, we propose a novel gradient entropy metric and p-Laplace diffusion constraint-based method…”
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Constraint-based inference algorithms for structural models with latent confounders— empirical application and simulations by Temme, Dirk

“… In this study, we apply the constraint based Fast Causal Inference algorithm implemented in the software program TETRAD on a data set containing strategy and performance information about 608 business units…”
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An Epsilon constraint-based evolutionary algorithm and multi-objective quality metrics for combined economic emission dispatch problem by Chan, Kit Yan, Yiu, Ka Fai Cedric, Kim, Dowon

“… Decision-makers can select solutions based on their preferences. This paper proposes an Epsilon-based multi-objective genetic algorithm (MOGA…”
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A constraint-based genetic algorithm for optimizing neural network architectures for detection of loss of coolant accidents of nuclear power plants by Tian, David, Deng, Jiamei, Vinod, Gopika, Santhosh, T.V., Tawfik, Hissam

“… This paper proposes a constraint-based genetic algorithm (GA) to find optimised 2-hidden layer network architectures for detecting LOCA of a NPP…”
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A novel constraint-based structure learning algorithm using marginal causal prior knowledge by Yu, Yifan, Hou, Lei, Liu, Xinhui, Wu, Sijia, Li, Hongkai, Xue, Fuzhong

“… We propose the Marginal Prior Causal Knowledge PC (MPPC) algorithm to incorporate marginal causal relations into a constraint-based structure learning algorithm…”
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Integrated constraint based clustering algorithm for high dimensional data by Liu, Xinyue, Li, Menggang

“… However, these constraint based algorithms use constraints to help accomplish only one of the three essential tasks…”
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Ground Constraint-Based LiDAR SLAM Algorithm for Outdoor Mobile Robots by Xiang, Shuqin, Sun, Shaoxin, Tan, Jian, Zhao, Xianghua, Wang, Weiguo

“… This paper proposes a LiDAR SLAM algorithm for outdoor mobile robots based on ground constraints…”
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Low-rank-constraint-based machine vision algorithm for chaffer-sieve-clogging recognition of corn harvester by Zhao, Rongqiang, Fu, Jun, Chen, Zhi, Tian, Lei, Ren, Luquan

“…[Display omitted] •The low-rank-constraint-based sieve clogging recognition algorithm is proposed…”
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A constraint-based search algorithm for parameter identification of environmental models by Gharari, S., Shafiei, M., Hrachowitz, M., Kumar, R., Fenicia, F., Gupta, H. V., Savenije, H. H. G.

“…, when making predictions in ungauged basins). In this study, we provide an alternative approach for parameter identification using constraints based on two types of restrictions derived from prior (or expert) knowledge…”
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A New Hybrid Brain MR Image Segmentation Algorithm with Super-Resolution, Spatial Constraint based Clustering and Fine Tuning by Xia, Jing, Li, Xuemei, Chen, Guoning, Zhang, Caiming

“… In this paper, we propose a new hybrid algorithm for brain MR image segmentation, combining super-resolution, spatial constraint based clustering and fine-tuning…”
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A hybrid path planning algorithm considering AUV dynamic constraints based on improved A algorithm and APF algorithm by Zhang, Wei, Wang, Naixin, Wu, Wenhua

“… This paper aims to address the issue of significant path-tracking errors arising from the independent research of traditional path-planning algorithms and path-tracking techniques…”
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Constraint-based scheduling algorithm with the non-adjacency requirement for multi-flow AWG switches by Chen, Shuyue, Lea, Chin-Tau

“… Conventional constraint-based scheduling algorithms have two limitations. First, they assume each input (output…”
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A Novel Constraint-Based Knee- Guided Neuroevolutionary Algorithm for Context-Specific ECG Early Classification by Huang, Yu, Yen, Gary G., Tseng, Vincent S.

“…Cardiovascular diseases (CVDs) are considered the greatest threat to human life according to World Health Organization. Early classification of CVDs and the…”
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Solving machine-loading problem of a flexible manufacturing system with constraint-based genetic algorithm by Kumar, Akhilesh, Prakash, Tiwari, M.K., Shankar, Ravi, Baveja, Alok

“… conditional constraints. From the literature, it has been seen that simple genetic-algorithm-based heuristics for this problem lead to constraint violations and large number of generations…”
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An algorithm for constraint-based structural template matching: application to 3D templates with statistical analysis by Barker, Jonathan A., Thornton, Janet M.

“… Hence there is a need for a more flexible core algorithm upon which to build more sophisticated tools…”
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Improved K2 algorithm for Bayesian network structure learning by Behjati, Shahab, Beigy, Hamid

“…: constraint-based, score-based, and hybrid methods. The K2 algorithm, as a score-based algorithm, takes a random order of variables as input and its efficiency is strongly dependent on this ordering…”
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