Extended Thermodynamic Integration: Efficient Prediction of Lambda Derivatives at Nonsimulated Points

2016 ◽  
Vol 12 (9) ◽  
pp. 4476-4486 ◽  
Author(s):  
Anita de Ruiter ◽  
Chris Oostenbrink
Keyword(s):  
Thermodynamic Integration ◽  
Extended Thermodynamic ◽  
Efficient Prediction

scholarly journals Threshold Computation for Spatially Coupled Turbo-Like Codes on the AWGN Channel

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 240
Author(s):  
Muhammad Umar Farooq ◽  
Alexandre Graell i Amat ◽  
Michael Lentmaier
Keyword(s):  
Gaussian Noise ◽  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Maximum A Posteriori ◽  
Prediction Methods ◽  
Threshold Analysis ◽  
A Posteriori ◽  
Awgn Channel ◽  
Efficient Prediction ◽  
Binary Erasure Channel

In this paper, we perform a belief propagation (BP) decoding threshold analysis of spatially coupled (SC) turbo-like codes (TCs) (SC-TCs) on the additive white Gaussian noise (AWGN) channel. We review Monte-Carlo density evolution (MC-DE) and efficient prediction methods, which determine the BP thresholds of SC-TCs over the AWGN channel. We demonstrate that instead of performing time-consuming MC-DE computations, the BP threshold of SC-TCs over the AWGN channel can be predicted very efficiently from their binary erasure channel (BEC) thresholds. From threshold results, we conjecture that the similarity of MC-DE and predicted thresholds is related to the threshold saturation capability as well as capacity-approaching maximum a posteriori (MAP) performance of an SC-TC ensemble.

scholarly journals A Compensatory Fuzzy Logic Model in Technical Trading

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 36
Author(s):  
Norma P. Rodríguez-Cándido ◽  
Rafael A. Espin-Andrade ◽  
Efrain Solares ◽  
Witold Pedrycz
Keyword(s):  
Fuzzy Logic ◽  
Technical Analysis ◽  
Graphical Analysis ◽  
Logic Model ◽  
Financial Asset ◽  
Financial Assets ◽  
Novel Approach ◽  
Subjective Assessments ◽  
Efficient Prediction ◽  
High Degree

This work presents a novel approach to prediction of financial asset prices. Its main contribution is the combination of compensatory fuzzy logic and the classical technical analysis to build an efficient prediction model. The interpretability properties of the model allow its users to incorporate and consider virtually any set of rules from technical analysis, in addition to the investors’ knowledge related to the actual market conditions. This knowledge can be incorporated into the model in the form of subjective assessments made by investors. Such assessments can be obtained, for example, from the graphical analysis commonly performed by traders. The effectiveness of the model was assessed through its systematic application in the stock and cryptocurrency markets. From the results, we conclude that when the model shows a high degree of recommendation, the actual financial assets show high effectiveness.

Understanding defects in DSA: calculation of free energies of block copolymer DSA systems via thermodynamic integration of a mesoscale block-copolymer model

2014 ◽  
Author(s):  
Andrew J. Peters ◽  
Richard A. Lawson ◽  
Benjamin D. Nation ◽  
Peter J. Ludovice ◽  
Clifford L. Henderson
Keyword(s):  
Block Copolymer ◽  
Thermodynamic Integration ◽  
Free Energies

scholarly journals Efficient Prediction of Network Traffic for Real-Time Applications

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Muhammad Faisal Iqbal ◽  
Muhammad Zahid ◽  
Durdana Habib ◽  
Lizy Kurian John
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Power Management ◽  
Dynamic Resource Allocation ◽  
Computation Complexity ◽  
Real Time Traffic ◽  
Double Exponential ◽  
Efficient Prediction ◽  
Dynamic Resource ◽  
Double Exponential Smoothing

Accurate real-time traffic prediction is required in many networking applications like dynamic resource allocation and power management. This paper explores a number of predictors and searches for a predictor which has high accuracy and low computation complexity and power consumption. Many predictors from three different classes, including classic time series, artificial neural networks, and wavelet transform-based predictors, are compared. These predictors are evaluated using real network traces. Comparison of accuracy and cost, both in terms of computation complexity and power consumption, is presented. It is observed that a double exponential smoothing predictor provides a reasonable tradeoff between performance and cost overhead.

scholarly journals Efficient Prediction of Difficult Keyword Queries over Databases

2014 ◽  
Vol 26 (6) ◽  
pp. 1507-1520 ◽  
Author(s):  
Shiwen Cheng ◽  
Arash Termehchy ◽  
V. Hristidis
Keyword(s):  
Efficient Prediction

scholarly journals SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules

2019 ◽  
Vol 47 (W1) ◽  
pp. W357-W364 ◽  
Author(s):  
Antoine Daina ◽  
Olivier Michielin ◽  
Vincent Zoete
Keyword(s):  
Small Molecules ◽  
Predictive Performance ◽  
Web Interface ◽  
Protein Targets ◽  
Human Proteins ◽  
Speed Up ◽  
On Line ◽  
Efficient Prediction ◽  
2D And 3D ◽  
Similarity Thresholds

Abstract SwissTargetPrediction is a web tool, on-line since 2014, that aims to predict the most probable protein targets of small molecules. Predictions are based on the similarity principle, through reverse screening. Here, we describe the 2019 version, which represents a major update in terms of underlying data, backend and web interface. The bioactivity data were updated, the model retrained and similarity thresholds redefined. In the new version, the predictions are performed by searching for similar molecules, in 2D and 3D, within a larger collection of 376 342 compounds known to be experimentally active on an extended set of 3068 macromolecular targets. An efficient backend implementation allows to speed up the process that returns results for a druglike molecule on human proteins in 15–20 s. The refreshed web interface enhances user experience with new features for easy input and improved analysis. Interoperability capacity enables straightforward submission of any input or output molecule to other on-line computer-aided drug design tools, developed by the SIB Swiss Institute of Bioinformatics. High levels of predictive performance were maintained despite more extended biological and chemical spaces to be explored, e.g. achieving at least one correct human target in the top 15 predictions for >70% of external compounds. The new SwissTargetPrediction is available free of charge (www.swisstargetprediction.ch).

Sign in / Sign up

Export Citation Format

Share Document