Based on Correlation Analysis and K-Means: An Anomaly Detection Algorithm for Seasonal Time-Series Data

Xin Wang,Yingxue Yang,Xueshuang Ding,Yantao Zhao

#Anomaly detection #seasonal data #time series #DBSCAN #K-means

Forecasting the Spread of Viral Diseases in Jordan Using the SARIMA Statistical Model

Shahed Al-khateeb

#Time series model #Jordan #prediction #diseases #forecasting model #sarimax #seasonal autoregressive integrated moving-average with exogenous regressors

Turning Point Induced Knowledge Forecasting under Uncertainties (TrIK)

Jagtap Vinyak,Kulkarni Parag,Joshi Pallavi

#Time series forecasting #shoulder area #turning point #knowledge discovery #surprise #uncertainty

Turning Point Induced Knowledge Forecasting under Uncertainties (TrIK)

Jagtap Vinyak,Kulkarni Parag,Joshi Pallavi

#Time series forecasting #shoulder area #turning point #knowledge discovery #surprise #uncertainty

Li Junkui and Wang Yuanzhen

# Data mining # time series # similarity search # dynami c time warping # early abandon

Mohammed Awad

# Clustering # time series prediction # RBF neural netw orks

Haneen AlWazan1, Kais Ibraheem2, and AbdulGhafoor Salim1

#Fuzzy time series forecasting # genetic algorithms p rediction

Zuriani Mustaffa and Yuhanis Yusof

#ABC # LSSVM # financial time series prediction # param eter tuning

Forecasting of Chaotic Time Series Using RBF

Faculty of Engineering and Information Technology, Arab American University, Palestine

#Time series forecasting # RBF neural networks # genetic algorithms # hybrid approach

Enhanced Hybrid Prediction Models for Time Series Prediction

as artificial neural networks are considered to be better for prediction of data with non-linear patterns. In the real-life, time-

#Hybrid model # adaptive neuro-fuzzy inference systems # soft computing # neural network # statistical techniques

Financial Time Series Forecasting Using Hybrid

School of Computing, University Union, Serbia

#Time-series forecasting # wavelet packet transform # neural networks

A Hybrid Approach for Modeling Financial Time Series

Faculty of Mathematics and Computer Science, Ovidi us University from Constanta, Romania

# Financial time series # forecasting # ARMA # GEP # hybr id methodology

Parameter Tuning of Neural Network for Financial Time Series Forecasting

Zeinab Fallahshojaei1 and Mehdi Sadeghzadeh2 1Department of Computer Engineering, Buin Zahra Branch, Islamic Azad University, Buin Zahra, Iran 2Department of Computer Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran

#Financial times series forecasting # parameter setting # NN # HS # parameter adaptation

Optimal Threshold Value Determination for Land Change Detection

Sangram Panigrahi1, Kesari Verma1, and Priyanka Tripathi2 1Department of Computer Applications, National Institute of Technology Raipur, India 2Department of Computer Engineering and Applications, National Institute of Technical Teachers

#Data mining # threshold determination # EVI and NDVI time series data # high dimensional data # land change detection # recursive search algorithm # recursive merging algorithm

An Improved Quantile-Point-Based Evolutionary

Segmentation Representation Method of Financial, Zheng Pei, Peng Chen*, Zhisheng Gao, Zhihao Gan, Kang Feng,

#Time series # feature representation # quantile segmentation points # linear segmentation # genetic algorithm

Echo State Network Optimization using Hybrid- Structure Based Gravitational Search Algorithm with Square Quadratic Programming for Time Series Prediction

Zohaib Ahmad,Muhammad Qasim Memon,Aasma Memon,Parveen Munshi,Muhammad jaffar Memon

#Echo state network #hybrid gravitational search algorithm #network configuration optimization #time series prediction

A Modified DBSCAN Algorithm for Anomaly Detection in Time-series Data with Seasonality

Praphula Jain,Mani Shankar Bajpai,Rajendra Pamula

#Anomaly detection #data mining #DBSCAN #modified DBSCAN #seasonal data #time series