Results 51 to 60 of about 397,119 (307)

Time Series Prediction Based on Complex-Valued S-System Model

Complexity, 2020
Symbolic regression has been utilized to infer mathematical formulas in order to solve the complex prediction and classification problems. In this paper, complex-valued S-system model (CVSS) is proposed to predict real-valued time series data.
Bin Yang, Wenzheng Bao, Yuehui Chen
doaj   +1 more source

Hetero-Dimensional Multitask Neuroevolution for Chaotic Time Series Prediction

IEEE Access, 2020
Chaotic time series prediction has important research and application value, and neural network-based prediction methods have problems such as low accuracy and difficulty in determining the number of nodes in the hidden layer.
Daoqing Zhang, Mingyan Jiang
doaj   +1 more source

Patient‐specific pharmacogenomics demonstrates xCT as predictive therapeutic target in colon cancer with possible implications in tumor connectivity

Molecular Oncology, EarlyView.
This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker, Keren Zohar, Martin Böttcher, Thomas Wartmann, Henry Freudenstein, Maximilian Doelling, Mihailo Andric, Wenjie Shi, Or Kakhlon, Katrin Hippe, Beatrix Jahnke, Dimitrios Mougiakakos, Franziska Baenke, Daniel Stange, Roland S. Croner, Michal Linial, Ulf D. Kahlert   +16 more
wiley   +1 more source

Chaotic time series. Part II. System Identification and Prediction [PDF]

Modeling, Identification and Control, 1994
This paper is the second in a series of two, and describes the current state of the art in modeling and prediction of chaotic time series. Sample data from deterministic non-linear systems may look stochastic when analysed with linear methods.
Bjørn Lillekjendlie, Dimitris Kugiumtzis, Nils Christophersen   +2 more
doaj   +1 more source

Aggressive prostate cancer is associated with pericyte dysfunction

Molecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero, Ane Martinez‐Larrinaga, Joaquim Grego‐Bessa, Saioa Garcia‐Longarte, Hielke van Splunder, Ianire Astobiza, Amaia Ercilla, Laura Bozal‐Basterra, Isabel Mendizabal, Pilar Villacampa, Arkaitz Carracedo, Mariona Graupera   +11 more
wiley   +1 more source

Levenberg-Marquardt Algorithm for Mackey-Glass Chaotic Time Series Prediction

Discrete Dynamics in Nature and Society, 2014
For decades, Mackey-Glass chaotic time series prediction has attracted more and more attention. When the multilayer perceptron is used to predict the Mackey-Glass chaotic time series, what we should do is to minimize the loss function.
Junsheng Zhao, Yongmin Li, Xingjiang Yu, Xingfang Zhang   +3 more
doaj   +1 more source

Liquid biopsy epigenetics: establishing a molecular profile based on cell‐free DNA

Molecular Oncology, EarlyView.
Cell‐free DNA (cfDNA) fragments in plasma from cancer patients carry epigenetic signatures reflecting their cells of origin. These epigenetic features include DNA methylation, nucleosome modifications, and variations in fragmentation. This review describes the biological properties of each feature and explores optimal strategies for harnessing cfDNA ...
Christoffer Trier Maansson, Anders Lade Nielsen, Boe Sandahl Sorensen   +2 more
wiley   +1 more source

A sequential coastal current prediction approach based on hierarchical decomposition

Frontiers in Marine Science
Precise prediction of coastal tidal current is essential for the efficient operation of tidal power generation, coastal engineering and maritime activities.
Nini Wang
doaj   +1 more source

Carbon Footprint Prediction in the Philippines Using Time Series in Data Science [PDF]

, 2023
Sweethy Jhoden Lim, Ma. Mica Ella Cortez, Rosanna Esquivel   +2 more
openalex   +1 more source

Time series prediction using ICA algorithms

Second IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2003. Proceedings, 2004
In this paper we propose a new method for volatile time series forecasting using Independent Component Analysis (ICA) algorithms and Savitzky-Golay filtering as preprocessing tools. The preprocessed data will be introduce in a based radial basis functions (RBF) Artificial Neural Network (ANN) and the prediction result will be compared with the one we ...
Juan M. Gorriz, Carlos G. Puntonet, Moises Salmeron, E. W. Lang   +3 more
openaire   +2 more sources