№ files_lp_4_process_1_47972
File format: docx
Character count: 9682
File size: 1598 KB
Year:
2023
Region / City:
Global
Topic:
Weather Forecasting, Machine Learning
Document Type:
Research Paper
Organization / Institution:
Not specified
Author:
Not specified
Target Audience:
Researchers, Meteorologists, Machine Learning Practitioners
Period of Validity:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Keywords:
Weather forecasting, Regression Techniques, Prediction, MSE
Context:
The document presents a research study on applying machine learning regression techniques for real-time weather forecasting and prediction.
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The product description is provided for reference. Actual content and formatting may differ slightly.
Year:
2025
Region / City:
California
Theme:
Energy, Forecasting, Grid Operations, Renewable Energy
Document Type:
Grant Funding Opportunity
Organization:
California Energy Commission
Author:
California Energy Commission
Target Audience:
Researchers, Utilities, Energy Market Participants, Policy Makers
Period of Validity:
October 2025 onwards
Approval Date:
October 2025
Date of Modifications:
N/A
Year:
2023
Region / City:
Not specified
Topic:
Demand forecasting, inventory management, machine learning, supply chain optimization
Document Type:
Review paper
Author:
Not specified
Target Audience:
Researchers, supply chain practitioners
Period of Action:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Year:
2024-2025
Region / City:
Florida
Subject:
Transportation forecasting, travel demand modeling
Document Type:
Work Plan
Organization / Institution:
Florida Department of Transportation (FDOT)
Author:
Florida Transportation Forecasting Forum (TFF)
Target Audience:
Transportation planners, engineers, decision-makers, modeling professionals
Period of Validity:
2024-2025
Approval Date:
Not specified
Date of Changes:
Not specified
Year:
2024
Region / City:
Nigeria
Topic:
Hydrology, Aquifers, Marine Science
Document Type:
Report
Author:
Not specified
Target Audience:
Researchers, Hydrologists, Marine Scientists
Period of Validity:
June 2024
Approval Date:
Not specified
Modification Date:
Not specified
Year:
Not specified
Region / City:
Not specified
Topic:
Weather forecasting, meteorology
Document Type:
Lab report
Organization / Institution:
University of Illinois
Author:
Not specified
Target Audience:
Students studying meteorology
Period of validity:
Not specified
Approval Date:
Not specified
Modification Date:
Not specified
Year:
2022
Region / City:
United States
Topic:
Climate-Informed Forecasting, Epidemiology, West Nile Virus
Document Type:
Scientific Research
Institution:
R Core Team, Goodrich et al.
Author:
Not specified
Target Audience:
Researchers, epidemiologists, climate scientists
Period of Validity:
2022
Date of Approval:
Not specified
Date of Changes:
Not specified
Year:
N/A
Region / City:
N/A
Theme:
Forecasting Techniques
Document Type:
Exam Questions
Organization / Institution:
N/A
Author:
Scott Stevens
Target Audience:
Students
Period of Action:
N/A
Approval Date:
N/A
Date of Changes:
N/A
Authors:
Vineeta Prakaulya; Prof. Roopesh Sharma; Upendra Singh; Ravikant Itare
Affiliation:
Patel College of Science and Technology, Indore
Department:
Computer Science and Engineering (CSE)
Document Type:
Review Article
Subject Area:
Data Mining and Climate Forecasting
Keywords:
Data mining, agriculture, soil fertility, crop yield, ANNs, FIS, LVQ, bi clustering
Geographical Focus:
India
Thematic Focus:
Precipitation prediction and agricultural productivity
Methods Discussed:
Artificial Neural Networks (ANNs), Fuzzy Inference System (FIS), Decision Tree (SLIQ), Time Series Analysis, Learning Vector Quantization (LVQ), Support Vector Machine (SVM), Bi-clustering
Data Scope:
Historical precipitation data including 45-year monsoon records and monthly precipitation series (1956–2008)
Intended Audience:
Researchers and practitioners in data mining, meteorology, and agricultural management
Chapter:
12
Subject:
Forecasting
Discipline:
Operations Management
Type of document:
Educational textbook exercises with solutions
Topics covered:
Moving average; Exponential smoothing; Adjusted exponential smoothing; Seasonal forecasting; Linear trend line; Linear regression; Multiple regression; Forecast accuracy measures; Control charts
Statistical measures:
MAD; Cumulative error (E); Average error (Ē); Correlation coefficient; Coefficient of determination
Organizations mentioned:
Tech; Bee Line Café; ITown; State University
Time references:
Eight semesters; Twelve quarters; Ten years; Forecast for 2005; Forecast for year 11
Software referenced:
Excel
Intended audience:
Students of operations management
Year:
2019
Region / City:
Australia
Topic:
Tobacco Excise
Document Type:
Working Paper
Organization:
The Treasury
Author:
Jonathan O’Bannon, John Clark
Target Audience:
Government policy makers, economists
Period of Validity:
Ongoing
Approval Date:
June 2019
Date of Modifications:
N/A
Year:
2023
Region / City:
Glassboro, NJ, USA
Theme:
Environmental Impact, Life Cycle Assessment, Machine Learning
Document Type:
Research Article
Organization / Institution:
Rowan University
Author:
Harriet Dufie Appiah, Matthew Conway, Jahnvi Patel, Marcella McMahon, Robert Hesketh, Kirti M. Yenkie
Target Audience:
Researchers, Environmental Scientists, Engineers
Period of Action:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Keywords:
Life Cycle Assessment, Machine Learning, Environmental Impact, Emissions
Contextual Description:
A research article discussing the application of machine learning models to predict environmental impacts of chemicals at the early design stage based on their molecular properties and life cycle data.
Year:
2023
Region / City:
Aurangabad District, Maharashtra
Subject:
Potential Evapotranspiration Forecasting
Document Type:
Research Article
Author:
Not specified
Target Audience:
Researchers, Hydrologists, Water Resource Managers
Period of Study:
1970–2023
Date of Approval:
Not specified
Date of Modifications:
Not specified
Keywords:
PET Forecasting, ANN, Thornthwaite Method, Water Resource Management
Year:
1998
Region / City:
Global
Subject:
Demand Forecasting
Document Type:
Educational Text
Institution:
Not specified
Author:
Not specified
Target Audience:
Students, Business Professionals
Period of Validity:
Not specified
Approval Date:
Not specified
Modification Date:
Not specified
Year:
2023
Region / City:
Aurangabad, Marathwada region, Maharashtra
Theme:
Water resource management, Evapotranspiration forecasting, Agricultural planning
Document type:
Research article
Organization / Institution:
Not specified
Author:
Not specified
Target Audience:
Researchers, water resource managers, agricultural planners
Period of validity:
1970-2023
Approval date:
Not specified
Date of modifications:
Not specified
Methodology:
Thornthwaite method, Artificial Neural Network (ANN)
Keywords:
Potential Evapotranspiration, Artificial Neural Network, Thornthwaite method, Time series analysis, Hydrological forecasting
Note:
Contextual description
Year:
2020
Region / City:
Kochi, Kerala
Topic:
Price Forecasting, Black Pepper Industry
Document Type:
Research Article
Organization / Institution:
Kamaraj College of Engineering and Technology, India
Author:
K. Kannan
Target Audience:
Researchers, Spice Industry Stakeholders
Period of Validity:
January to December 2020
Approval Date:
Not specified
Date of Changes:
Not specified
Confidentiality Level:
BL - Restricted for internal use
TC ID / Revision:
00153898/C
Document Status:
Document Released
Document No.:
N/A
WBS code:
5.2 - RP3 Particle acceleration by lasers
PBS code:
E.E4.ELMA.4.5.4
Project branch:
Engineering & Scientific documents (E&S)
Document Type:
Specification (SP)
Position:
Senior researcher
Prepared by:
Senior researcher Valentina Scuderi
Reviewed By:
Daniele Margarone, Ladislav Půst, Pavel Bastl, Roman Kuřátko, Tomáš Laštovička, Veronika Olšovcová, Viktor Fedosov
Approved by:
Georg Korn
Revision History / Change Log:
D. Margarone, V. Scuderi, A. Kuzmenko
Date of Creation:
26.07.2017
Date of Last Modification:
22.08.2017
Change Description:
RSD draft creation, RSD update, formal update for approval
Introduction:
The Requirements Specification Document (RSD) details technical requirements and constraints for the Real-time Digital Oscilloscope to be purchased for the ELI Beamlines project.
Purpose:
The document defines the functional, performance, safety, and quality requirements for the Oscilloscope.
Scope:
The Oscilloscope specifications include performance standards, interface needs, power supply compatibility, safety, and delivery requirements.
Terms, Definitions and Abbreviations:
AC, BW, CA, Ch, CPU, DC, ELI, GND, pts, RMS, RSD, USB, WXGA
References to standards:
This document permits alternatives to specified standards if they are equivalently proven by the supplier.
Functional, Performance and Design requirements:
Includes minimum specifications for bandwidth, vertical resolution, sample rate, memory, sensitivity, and accuracy of the Oscilloscope.
Interface requirements:
Specifies connectivity options such as Ethernet and USB, and software compatibility with Windows 7.
Power supply:
The Oscilloscope is compatible with a wide range of AC input voltages and has specified power consumption limits.
Delivery requirements:
Delivery of the Oscilloscope must be managed by the Supplier to the ELI Beamlines final destination.
Safety Requirements:
Supplier must provide a Declaration of Conformity or equivalent documentation for compliance with EU regulations.
Quality Requirements:
The Supplier must provide user manuals, calibration certificates, and proof of outgoing checks, as well as ensure non-conformance control and warranty repair procedures.
Year:
2012
Region / City:
United States
Topic:
Real-Time Location Systems (RTLS) for VA
Document Type:
Performance Work Statement
Agency:
Department of Veterans Affairs
Author:
Not specified
Target Audience:
Veterans Health Administration, VA personnel, contractors, and technology vendors
Period of Effect:
Not specified
Approval Date:
February 24, 2012
Modification Date:
Not specified
Note:
Year
Countries & Regions:
Asia Pacific, Southern and Eastern Africa, West and Central Africa, Eastern Mediterranean and Middle East and North Africa, Afghanistan, Bangladesh, Burkina Faso, Burundi, Cameroon, Ethiopia, Fiji, Indonesia, Lao PDR, Libya, Myanmar, Nepal, occupied Palestinian territory (oPt), Pakistan, Papua New Guinea, Philippines, Somalia, South Sudan, Sri Lanka, Sudan, Syria (cross-border operation from Gaziantep), Vanuatu, Yemen
Year:
2019
Region / City:
USA, Virginia
Topic:
Real-time video in medical imaging
Document Type:
Technical standard
Organization / Institution:
DICOM Standards Committee, NEMA
Author:
DICOM Standards Committee
Target Audience:
Medical professionals, healthcare technology developers
Effective Period:
Not specified
Approval Date:
September 16, 2019
Amendment Date:
Not specified
Organization:
DICOM Standards Committee
Working Group:
Working Group 13
Standard series:
NEMA Standards Publication PS 3
Supplement number:
202
Title:
Real-Time Video
Version:
Draft Letter Ballot
Date:
May 23–24, 2019
Status:
Draft document
Work item:
DICOM Workitem 2016-12-D
Location:
Rosslyn, Virginia, USA
Copyright holder:
NEMA
Copyright year:
2018
Scope:
Real-time transport, metadata, and representation of video and audio in DICOM
Related standards:
SMPTE ST 2110 series
Document type:
Technical standard supplement
Target domain:
Medical imaging and real-time clinical video
Informative and normative content:
Mixed