Stem forecast$ (all stems)

77 papers:

CASE-2015-CheongSB #ad hoc #automation #optimisation

Ad-hoc automated teller machine failure forecast and field service optimization (MLFC, KPS, BCB), pp. 1427–1433.

SIGMOD-2015-SakuraiMF #mining

Mining and Forecasting of Big Time-series Data (YS, YM, CF), pp. 919–922.

CHI-2015-KjeldskovSPLMN

Eco-Forecasting for Domestic Electricity Use (JK, MBS, JP, DL, TM, MN), pp. 1985–1988.

CHI-2015-SimmFFNFHD #energy #grid

Tiree Energy Pulse: Exploring Renewable Energy Forecasts on the Edge of the Grid (WS, MAF, AF, PN, SF, MH, AJD), pp. 1965–1974.

ICEIS-v1-2015-SouzaBGBE #learning #online

Applying Ensemble-based Online Learning Techniques on Crime Forecasting (AJdS, APB, HMG, JPB, FE), pp. 17–24.

KDD-2015-GroverKH #hybrid

A Deep Hybrid Model for Weather Forecasting (AG, AK, EH), pp. 379–386.

KDD-2015-YuW0PSIW #bound #markov #multi

Tornado Forecasting with Multiple Markov Boundaries (KY, DW, WD, JP, DLS, SI, XW), pp. 2237–2246.

KDD-2015-ZhaoSYCLR #learning #multi

Multi-Task Learning for Spatio-Temporal Event Forecasting (LZ, QS, JY, FC, CTL, NR), pp. 1503–1512.

KDD-2015-ZhengYLLSCL #big data #fine-grained #quality

Forecasting Fine-Grained Air Quality Based on Big Data (YZ, XY, ML, RL, ZS, EC, TL), pp. 2267–2276.

SAC-2015-FernandesPCRP #detection #metaheuristic #network #statistics

Statistical, forecasting and metaheuristic techniques for network anomaly detection (GF, EHMP, LFC, JJPCR, MLPJ), pp. 701–707.

SAC-2015-XuYYHHK #multi #predict #using

Solar irradiance forecasting using multi-layer cloud tracking and numerical weather prediction (JX, SY, DY, DH, JH, PK), pp. 2225–2230.

CASE-2014-LinW

Applications of data assimilation to forecasting indoor environment (CCL, LW), pp. 1097–1102.

CHI-2014-MasseyLW #repository

Cloudy forecast: an exploration of the factors underlying shared repository use (CM, TL, SW), pp. 2461–2470.

ICML-c1-2014-TaiebH #multi

Boosting multi-step autoregressive forecasts (SBT, RJH), pp. 109–117.

ICPR-2014-GoldhammerDBGS #network

Pedestrian’s Trajectory Forecast in Public Traffic with Artificial Neural Networks (MG, KD, UB, AG, BS), pp. 4110–4115.

KDD-2014-ChenN #detection #graph #parametricity #social #social media #statistics

Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs (FC, DBN), pp. 1166–1175.

KDD-2014-RamakrishnanBMSKSWCVKKMZHCLHSTGKDAZFSFAGM #open source #using

“Beating the news” with EMBERS: forecasting civil unrest using open source indicators (NR, PB, SM, NS, RPK, PS, WW, JC, AV, GK, CJK, AM, LZ, TH, FC, CTL, BH, AS, KT, LG, GK, AD, CA, IZ, JF, KMS, YF, JA, DG, DM), pp. 1799–1808.

SEKE-2014-FernandesALG #modelling #probability #process #reduction

A Dimensionality Reduction Process to Forecast Events through Stochastic Models (PF, JA, LL, SG), pp. 534–539.

SAC-2014-GeorgiadisP #algorithm #online #problem #scheduling #smarttech

Dealing with storage without forecasts in smart grids: problem transformation and online scheduling algorithm (GG, MP), pp. 518–524.

SAC-2014-PengYYHKH #3d #detection #multi #using

3D cloud detection and tracking for solar forecast using multiple sky imagers (ZP, SY, DY, DH, PK, JH), pp. 512–517.

ICML-c2-2013-Goerg #analysis #component

Forecastable Component Analysis (GMG), pp. 64–72.

ICML-c3-2013-WytockK #algorithm #energy #random #theory and practice

Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting (MW, JZK), pp. 1265–1273.

KDD-2013-MontgomerySCM #experience #predict

Experience from hosting a corporate prediction market: benefits beyond the forecasts (TAM, PMS, MJC, PEM), pp. 1384–1392.

KDD-2013-WangDYWCSI #clustering #data mining #framework #identification #mining #towards

Towards long-lead forecasting of extreme flood events: a data mining framework for precipitation cluster precursors identification (DW, WD, KY, XW, PC, DLS, SI), pp. 1285–1293.

MLDM-2013-BrownPD #algorithm #search-based

Dynamic-Radius Species-Conserving Genetic Algorithm for the Financial Forecasting of Dow Jones Index Stocks (MSB, MJP, HD), pp. 27–41.

MLDM-2013-HuSAD #network #performance #statistics

Estimating and Forecasting Network Traffic Performance Based on Statistical Patterns Observed in SNMP Data (KH, AS, DA, CD), pp. 601–615.

MLDM-2013-KoharaS #learning #self

Typhoon Damage Scale Forecasting with Self-Organizing Maps Trained by Selective Presentation Learning (KK, IS), pp. 16–26.

SAC-2013-IlicSKJ #algorithm #assessment

Impact assessment of smart meter grouping on the accuracy of forecasting algorithms (DI, PGdS, SK, MJ), pp. 673–679.

ASE-2012-AminGC #approach #automation #linear #modelling

An automated approach to forecasting QoS attributes based on linear and non-linear time series modeling (AA, LG, AC), pp. 130–139.

CASE-2012-BaoLYL #energy #programming #realtime

Battery energy storage system load shifting control based on real time load forecast and dynamic programming (GB, CL, ZY, ZL), pp. 815–820.

CASE-2012-YangTCHC

A dual-forecast scheme for production output with paired/unpaired WIP data (HCY, THT, CYC, MHH, FTC), pp. 581–586.

ICPR-2012-ZhangFLZG #online

Online ICP forecast for patients with traumatic brain injury (FZ, MF, LYL, ZZ, CG), pp. 37–40.

KDD-2012-MatsubaraSFIY #mining #performance

Fast mining and forecasting of complex time-stamped events (YM, YS, CF, TI, MY), pp. 271–279.

KDIR-2012-Martiny #security

Unsupervised Discovery of Significant Candlestick Patterns for Forecasting Security Price Movements (KM), pp. 145–150.

KDIR-2012-Zamora-MartinezRPT #empirical #network

Some Empirical Evaluations of a Temperature Forecasting Module based on Artificial Neural Networks for a Domotic Home Environment (FZM, PR, JP, DT), pp. 206–211.

SEKE-2012-DagninoSR #fault #machine learning #using

Forecasting Fault Events in Power Distribution Grids Using Machine Learning (AD, KS, LR), pp. 458–463.

HCD-2011-JungLCKLOCRKL #development

Development of Web-Based Participatory Trend Forecasting System: urtrend.net (ECJ, SL, HC, BK, HL, YO, YC, WR, HK, JYL), pp. 65–73.

ICEIS-v2-2011-LiangZL

Stock Market Forecasting based on Wavelet and Least Squares Support Vector Machine (XL, HZ, XL), pp. 46–53.

ICEIS-v2-2011-TarsauliyaTS #network #search-based #using

Financial Time Series Forecast using Simulated Annealing and Threshold Acceptance Genetic BPA Neural Network (AT, RT, AS), pp. 172–177.

ICEIS-v3-2011-HuXJ

Information Forecast in a Supply Chain with Electronic Market (PH, WX, LJ), pp. 507–510.

KDD-2011-CuiZLM #online

Bid landscape forecasting in online ad exchange marketplace (YC, RZ, WL, JM), pp. 265–273.

KDD-2011-LiLLNTF #cyber-physical #named

ThermoCast: a cyber-physical forecasting model for datacenters (LL, CJML, JL, SN, AT, CF), pp. 1370–1378.

SIGIR-2011-CetintasCSSD #modelling #online #probability

Forecasting counts of user visits for online display advertising with probabilistic latent class models (SC, DC, LS, BS, ZD), pp. 1217–1218.

SIGMOD-2010-AgarwalCLSV

Forecasting high-dimensional data (DA, DC, LjL, JS, EV), pp. 1003–1012.

CIKM-2010-VijayalakshmiMMDRM #algorithm #search-based #using

Intelligent sales forecasting engine using genetic algorithms (MV, BM, RM, AD, RR, KM), pp. 1669–1672.

ICPR-2010-KoprinskaSA

Variable Selection for Five-Minute Ahead Electricity Load Forecasting (IK, RS, VGA), pp. 2901–2904.

SAC-2010-SantanaLM #clustering #realtime #web

Load forecasting applied to soft real-time web clusters (CS, JCBL, DM), pp. 346–350.

CASE-2009-Srinidhi #development

Development of an airline traffic forecasting model on international sectors (SS), pp. 322–327.

SAC-2009-ChengS #modelling #nondeterminism #quality

Uncertainty apportionment for air quality forecast models (HC, AS), pp. 956–960.

SAC-2009-MasaruS #algorithm #modelling #search-based

Daily demand forecasting of new products utilizing diffusion models and genetic algorithms (TM, MS), pp. 1106–1107.

VLDB-2008-GeZ #approach #query

A skip-list approach for efficiently processing forecasting queries (TG, SBZ), pp. 984–995.

VLDB-2008-TeubnerGMS #xquery

Dependable cardinality forecasts for XQuery (JT, TG, SM, SS), pp. 463–477.

ICEIS-AIDSS-2008-Nachev #network #using

Forecasting with ARTMAP-IC Neural Networks — An Application Using Corporate Bankruptcy Data (AN), pp. 167–172.

CIKM-2008-WangBFJ

A note on search based forecasting of ad volume in contextual advertising (XW, AZB, MF, VJ), pp. 1343–1344.

KDD-2008-ChengT #learning

Semi-supervised learning with data calibration for long-term time series forecasting (HC, PNT), pp. 133–141.

CASE-2007-HablaDMPE

A Short-Term Forecast Method for Demand Quantities in Semiconductor Manufacturing (CH, RD, LM, TP, HE), pp. 94–99.

CASE-2007-YipLL #process

Forecasting Final/Class Yield Based on Fabrication Process E-Test and Sort Data (WKY, KGL, WJL), pp. 478–483.

VLDB-2007-DuanB #query

Processing Forecasting Queries (SD, SB), pp. 711–722.

MSR-2007-HerraizGR07a #analysis #eclipse #using

Forecasting the Number of Changes in Eclipse Using Time Series Analysis (IH, JMGB, GR), p. 32.

MLDM-2007-AburtoW #hybrid #predict

A Sequential Hybrid Forecasting System for Demand Prediction (LA, RW), pp. 518–532.

KDD-2006-JankSW #functional #modelling #online #realtime

Dynamic, real-time forecasting of online auctions via functional models (WJ, GS, SW), pp. 580–585.

CASE-2005-ViswanathanF

Forecasting of service arrivals in a repair center (SV, YF), pp. 285–289.

KDD-2005-PowersGC #enterprise #performance

Short term performance forecasting in enterprise systems (RP, MG, IC), pp. 801–807.

ICEIS-v1-2004-MagnussonNC #concept #enterprise #framework #implementation #towards

A Conceptual Framework for Forecasting ERP Implementation Success — A First Step Towards the Creation of an Implementation Support Tool (JM, AN, FC), pp. 447–453.

ICEIS-v2-2004-CamargoFPS #network #tool support

Neural Network and Time Series as Tools for Sales Forecasting (MC, WPF, MP, AS), pp. 476–478.

CIKM-2002-ChakrabartiF #automation #named #scalability #using

F4: large-scale automated forecasting using fractals (DC, CF), pp. 2–9.

KDD-2001-HueglinV #data mining #mining

Data mining techniques to improve forecast accuracy in airline business (CH, FV), pp. 438–442.

KDD-2001-PennockLNG #game studies #probability #web

Extracting collective probabilistic forecasts from web games (DMP, SL, FÅN, CLG), pp. 174–183.

ICPR-v2-2000-JainJV #experience #network #using

Short-Term Water Demand Forecasting Using Artificial Neural Networks: IIT Kanpur Experience (AJ, UCJ, AKV), pp. 2459–2462.

ICPR-v2-2000-LaiCF #canonical #correlation #using

Power Load Forecasting Using Neural Canonical Correlates (PLL, SJC, CF), pp. 2455–2458.

ICPR-v4-2000-LaiLCCW #pattern matching #pattern recognition #recognition

Pattern Recognition of Radar Echoes for Short-Range Rainfall Forecast (ESTL, PWL, CMC, MCC, WHW), pp. 4299–4302.

ICPR-1998-SinghS #pattern matching

A pattern matching tool for time-series forecasting (SS, ES), pp. 103–105.

KDD-1998-RaoRC #adaptation #multi

Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers (RBR, SR, FC), pp. 319–323.

HPDC-1997-Wolski #network #performance #scheduling #using

Forecasting Network Performance to Support Dynamic Scheduling using the Network Weather Service (RW), pp. 316–325.

WIA-1996-BoneDGM #automaton #finite

Time Series Forecasting by Finite-State Automata (RB, CD, AG, DM), pp. 26–34.

SAC-1994-MahoneyLW #exponential #network

Construction of an artificial neural network for simple exponential smoothing in forecasting (DWM, RPL, SIW), pp. 308–312.

SAC-1993-ShnaiderHS

Expert Systems for Economic/Business Forecasting (ES, PH, MS), pp. 511–516.