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15.519  Articles
1 of 1.553 pages  |  10  records  |  more records»
Accounting is an important management discipline with strong theoretical foundation and practical operation. Due to the differences between individuals in the process of learning, the mastery of the subject is different. This requires teachers to implemen... see more

Bayesian network structure learning from data has been proved to be a NP-hard (Non-deterministic Polynomial-hard) problem. An effective method of improving the accuracy of Bayesian network structure is using experts’ knowledge instead of only using ... see more

Dipterocarpaceae is one of the most prominent plant families, with more than 500 members of species. This family mostly used timber plants for housing, making ships, decking, and primary materials for making furniture. In Indonesia, many Dipterocarpaceae ... see more

Dipterocarpaceae is one of the most prominent plant families, with more than 500 members of species. This family mostly used timber plants for housing, making ships, decking, and primary materials for making furniture. In Indonesia, many Dipterocarpaceae ... see more

Divert attitude and control system (DACS) is a one-shot system and provides attitude correction and translation of the Launch vehicle. DACS consists of many flight critical sub systems which are arranged in a series configuration. The traditional Reliabil... see more

The Bayesian researcher should know the basic ideas underlying Bayesian methodology and the computational tools used in modern Bayesian econometrics.  Some of the most important methods of posterior simulation are Monte Carlo integration, importance ... see more

K-mer frequencies are commonly used in extracting features from metagenome fragments. In spite of this, researchers have found that their use is still inefficient. In this research, a genetic algorithm was employed to find optimally spaced k-mers. These w... see more

Bayesian networks (BNs) are one of the most widely used class for machine learning and decision making tasks especially in uncertain domains. However, learning BN structure from data is a typical NP-hard problem. In this paper, we present a novel hybrid a... see more

Hyperparameter selection has always been the key to machine learning. The Bayesian optimization algorithm has recently achieved great success, but it has certain constraints and limitations in selecting hyperparameters. In response to these constraints an... see more

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