Results 31 to 40 of about 7,967,373 (246)
PENILAIAN KEBUTUHAN PEMANFAATAN E-LEARNING [PDF]
, 2014 : This research aims to get a description of State University of Jakarta (UNJ) readiness to take advantage of e-learning in implementation of lecture viewed from some aspects both institutional, technological, and pedagogical.
Khaerudin Khaerudin +1 more
core +1 more source
Bayesian Network Parameter Learning Method on Small Samples [PDF]
Jisuanji gongcheng, 2016 Maximum likelihood estimation is a classical and effective method for Bayesian network parameter learning on large samples,but it is not consistent when learning on small sample with little expertise.To address the issue,a novel method called TL-WMLE is ...
LI Zida,LIAO Shizhong
doaj +1 more source
PbP2: Automatic Configuration of a Portfolio-based Multi-Planner [PDF]
We present PbP2, an automated system that generates efficient domain-specific multi planners from a portfolio of domain-independent planning techniques by (i) computing some sets of macro-actions for every planner in the portfolio, (ii) optimizing the ...
Vallati, Mauro +2 more
core +3 more sources
Bayesian Analysis of Bubbles in Asset Prices
Econometrics, 2017 We develop a new model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a
Andras Fulop, Jun Yu
doaj +1 more source
A machine learning approach to Bayesian parameter estimation
npj Quantum Information, 2021 Bayesian estimation is a powerful theoretical paradigm for the operation of the approach to parameter estimation. However, the Bayesian method for statistical inference generally suffers from demanding calibration requirements that have so far restricted
Samuel Nolan +2 more
doaj +1 more source
An Adaptive Linear Programming Algorithm with Parameter Learning
AlgorithmsWhen dealing with engineering design problems, designers often encounter nonlinear and nonconvex features, multiple objectives, coupled decision making, and various levels of fidelity of sub-systems.
Lin Guo +4 more
doaj +1 more source
Seismic Signal Classification Using Perceptron With Different Learning Rules
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Perceptron is adopted to classify the Ricker wavelets and to detect the seismic anomaly in a seismogram. Three learning rules are used in the training of perceptron to solve the decision boundary. The optimal learning-rate parameter is derived. The lower
Kou-Yuan Huang +2 more
doaj +1 more source
Generalized Bayes Estimation Based on a Joint Type-II Censored Sample from K-Exponential Populations
Mathematics, 2023 Generalized Bayes is a Bayesian study based on a learning rate parameter. This paper considers a generalized Bayes estimation to study the effect of the learning rate parameter on the estimation results based on a joint censored sample of type-II ...
Yahia Abdel-Aty +2 more
doaj +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source