Random process models

Anomaly detection for Internet of things (IoT) networks is a challenging issue due to the huge number of devices that connect to each other and generate huge amounts of data. In this study, we propose a model combining Autoencoder (AE) with classification algorithms to build an endto-end architecture for processing, feature extraction and data classification.

13p viambani 18-06-2024 7 1   Download

Ebook "Partitions, hypergeometric systems, and dirichlet processes in statistics" focuses on statistical inferences related to various combinatorial stochastic processes. Specifically, it discusses the intersection of three subjects that are generally studied independently of each other: partitions, hypergeometric systems, and Dirichlet processes. The Gibbs partition is a family of measures on integer partition, and several prior processes, such as the Dirichlet process, naturally appear in connection with infinite exchangeable Gibbs partitions.

140p tracanhphuonghoa1007 22-04-2024 5 2   Download

Ebook "Classical and spatial stochastic processes: With applications to biology (Second edition)" presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling. While still treating many important problems in fields such as engineering and mathematical physics, the book also focuses on the highly relevant topics of cancerous mutations, influenza evolution, drug resistance, and immune response.

271p manmanthanhla0201 26-02-2024 4 1   Download

Part 1 of ebook "Reliability and statistics in geotechnical engineering" provides readers with content including: tntroduction – uncertainty and risk in geotechnical engineering; uncertainty; probability; inference; risk, decisions and judgment;...

314p dieptieuung 19-07-2023 8 4   Download

Continued part 1, part 2 of ebook "Basic concepts in computational physics (Second edition)" has presents the following content: stochastic methods; pseudo-random number generators; random sampling methods; a brief introduction to monte-carlo methods; the ising model; some basics of stochastic processes; the random walk and diffusion theory; markov-chain monte carlo and the potts model; data analysis; stochastic optimization; the two-body problem;...

221p dieptieuung 20-07-2023 9 3   Download

Undirected graphical models or Markov random fields have been a popular class of models for representing conditional dependence relationships between nodes. In particular, Markov networks help us to understand complex interactions between genes in biological processes of a cell.

10p vinarcissa 21-03-2023 5 1   Download

Lecture Physiological signal processing - Chapter 7: Random signals. This chapter will cover the following: probability models and random variables; jointly distributed random variables; linear estimation; random processes; estimation of mean, variance, and covariance;... Please refer to the chapter for details!

104p chutieubang 06-12-2022 5 3   Download

This study analyzes the literature review of the techniques for estimating Height Equivalent Theoretical Plate (HETP) values for various packing structure models, ranging from theoretical to semi-empirical to shortcut methods. Packing structures of various meshes and shapes were studied on the purification of benzaldehyde from the mixture of benzaldehyde and cinnamaldehyde.

8p viporsche 25-10-2022 7 3   Download

Many stochastic processes in practice having the sequences of random variables are generally skewed and dependent and to solve these problems, the application of first-order gamma autoregressive (GAR(1)) model[4] is very effective; especially in the study of streamflow simulation in Stochastic Hydrology. This paper mainly presents the study of Gar(1) model in the simulation of monthly streamflows. To reach this aim, we study Thomas-Fiering model and proposed the Gar(1)-Fragments model.

6p vikoenigsegg 29-09-2022 11 2   Download

Three main approaches have been generally proposed to the flood forecasting including: i) physical models, ii) statistical models and iii) data-driven models. The first approaches, also called hydraulic models, aims to reproduce the hydrological processes in a physically realistic manner and is based on mathematical formulas of conservation of mass, momentum and energy.

3p vipriyankagandhi 27-07-2022 4 1   Download

Frailty is characterized by an age-related decline in multiple physiological systems, leading to a high vulnerability to stressors, adverse health outcomes, and low quality of life. Neuroscientific models of pathological aging emphasize the loss of sensorimotor stimulation and reduced neuromodulatory capacities as core processes in age-related cognitive and bodily decline, which may be associated with maladaptive plastic changes in the brain.

13p vinobelprisen 26-03-2022 13 4   Download

Lecture Biomedical Signal Processing and Modeling: Filtering for Removal of Artifact - Nguyen Cong Phuong provide students with knowledge about introduction; random, structured, and physiological noise; illustration of the problem with case studies; fundamental concepts of filtering; time domain filters; frequency domain filters;...

165p tanmocphong 19-01-2022 13 0   Download

In the proposed solution, Random Forests are suggested as an e®ective ensemble model suitable for our heterogeneous data when many single prediction models which are random trees can be built for many various subspaces with di®erent random features in a supervised learning process.

19p redemption 20-12-2021 32 1   Download

In this study, 1000 data sets randomly generated by the FEM through iterations are used for the training process to get optimal weights. Based on these obtained optimal weights, beam behaviors under the changes in material distribution through thickness could then be predicted. In this model, the ANN’s inputs are the gradation index of the power-law distribution and thickness, while the outputs are compliance and beam displacements. The computed results are verified against those derived from the FEM.

12p inception36 30-11-2021 4 1   Download

The research used a descriptive research design utilizing an Input-Process-Output model conducted at University of Southeastern Philippines in its three campuses in Region XI, namely: Obrero, Mintal and Tagum-Mabini. Using a stratified random sampling method, 358 students were determined to be part of the respondents of the study.

6p trinhthamhodang11 04-05-2021 6 1   Download

This research aims to analyze the determinants of stock return disclosure of mining sector companies listed on the Indonesia Stock Exchange in 2014-2018. The research adopted the Eviews program in data processing and Random effect regression model was chosen to test the relationship between internal and external indicators as independent variables include return on asset (ROA), debt to equity ratio (DER), total asset turnover (TATO), oil price and exchange rate. The result shows that return on assets and debt to equity ratio have no effect on stock return.

5p caygaocaolon11 18-04-2021 38 6   Download

In this article, we investigate a risk model with a quota-(α, β) reinsurance contract. The premium process and claim process are assumed to be independent sequences of indentically distributed random variables. Using inductive method, we obtain upper bound of infinite-time ruin probability of an insurance company.

3p chauchaungayxua11 23-03-2021 11 2   Download

In air pollution studies at metropolis, as in Bangkok or Saigon, installation of new stations for monitoring dangerous pollution sources is costly. Using statistical models and analyzing data sets collected at good stations to predict air pollution levels at malfunctioning stations, therefore, are highly demanding. We study air pollution prediction by geo-statistical methods with a realistic dataset costly observed in Ho Chi Minh City.

23p trinhthamhodang9 10-12-2020 14 2   Download

Shrimp farming is a key sector in economic development in Mekong Delta provinces. Unfortunately, there are many problems in shrimp farming, especially shrimp diseases which cause a considerable loss. Shrimp diseases are expressed through symptoms and manifestations of shrimp.

8p quenchua9 20-11-2020 15 1   Download

The Random Forest (RF) algorithm for supervised machine learning is an ensemble learning method widely used in science and many other fields. Its popularity has been increasing, but relatively few studies address the parameter selection process: a critical step in model fitting.

13p vioklahoma2711 19-11-2020 11 0   Download