Copy Link
Add to Bookmark
Report
Neuron Digest Volume 11 Number 02
Neuron Digest Friday, 15 Jan 1993 Volume 11 : Issue 2
Today's Topics:
Grad studies in Cog Sci at U. Edinbugh
Building energy predictor Competition - "The Great Energy Shootout"
Send submissions, questions, address maintenance, and requests for old
issues to "neuron-request@cattell.psych.upenn.edu". The ftp archives are
available from cattell.psych.upenn.edu (130.91.68.31). Back issues
requested by mail will eventually be sent, but may take a while.
----------------------------------------------------------------------
Subject: Grad studies in Cog Sci at U. Edinbugh
From: rcs@cogsci.edinburgh.ac.uk
Date: Mon, 28 Dec 92 12:10:12 +0000
************************************************************************
POSTGRADUATE STUDY
IN THE
CENTRE FOR COGNITIVE SCIENCE
AT THE
UNIVERSITY OF EDINBURGH
The Centre for Cognitive Science (CCS) is devoted exclusively to research
and postgraduate teaching in Cognitive Science. The Centre's 20 lecturers
and research fellows work with over 40 postgraduates in a rich and varied
intellectual and social environment. Regular interdisciplinary research
workshops, in which students actively participate, focus on current
problems in Cognitive Science; speakers of international repute visit the
department regularly. Research projects, many of them collaborative with
other European centres of excellence, have been funded by ESRC, SERC,
ESPRIT and BRAIN in such areas as natural language understanding and
computational neuroscience.
The Postgraduate Programme in Cognitive Science: Central to the programme
is the study of language and the cognitive processes involved in its use.
The programme's aim is to provide students with a secure knowledge of the
principles and techniques underlying the four component disciplines:
Theoretical Linguistics
Logic and Formal Semantics
Computational Linguistics
Cognitive Psychology
The course: All first year students attend a one-term module in each
subject in the first term. In the second term there is an
interdisciplinary Theories of Mind seminar course, together with three
second term modules chosen from the four component disciplines plus a
Neural Nets module. In general, topics covered include: text
comprehension, memory, speech perception, human sentence processing,
cognitive modelling, neural nets, parsing algorithms, categorial
grammars, the mental lexicon and lexical access, linguistic universals
and parametric variation, unification and constraint-based grammars,
tense and modal logic, type theory, post-Montague semantics, partial
logics, and logic programming (e.g. Prolog).
In May, candidates sit written examinations based on material drawn from
the courses; they must also show a basic facility to program in Prolog,
for which there is an appropriate introductory course. Some of the
assessment is by means of term papers instead of exams. Successful
candidates then go on to work on an MSc dissertation, or are recommended
for registration for a PhD or MPhil. Advanced courses on specific topics
are available for second year PhD students.
Students who complete the course readily find employment in University
teaching, in funded research projects, and in industry.
Teaching staff:
Elisabet Engdahl [Head of Department]
linguistic theory, parametric variation, situation theory
Ellen Bard [Linguistics]
psycholinguistics, speech processing
Robin Cooper [Artificial Intelligence]
natural language semantics, situation theory, quantification
Matt Crocker [Artificial Intelligence]
principle-based parsing, computational psycholinguistics
Robert Dale [Artificial Intelligence]
language generation, discourse structure, intelligent text processing
Ewan Klein
linguistic theory, semantics of graphics, phonology
Brendan McGonigle [Psychology]
comparative cognitive development
Paul Schweizer [Director of Postgraduate Studies]
philosophical logic, modal logic, philosophy of language
Richard Shillcock
psycholinguistics, cognitive modelling
Keith Stenning [HCRC]
human memory, inference, connectionism
Henry Thompson [HCRC]
computational linguistics, speech processing
David Willshaw
neural nets, hippocampal function
Associates and Fellows:
Nick Chater [Psychology]
neural networks and cognitive psychology
Robert Ladd [Linguistics]
prosodic phonology
John Lee [Architecture]
graphics in communication and inferencing, HCI, computer-aided design
Gordon Plotkin [Computer Science]
semantics of programming languages
Chris Mellish [Artificial Intelligence]
parsing and generation
Co-operating departments: Artificial Intelligence, Computer Science
(LFCS), EdCAAD, Linguistics, Philosophy, and Psychology.
Human Communication Research Centre: Closely associated with CCS is the
HCRC, ESRC's centre of excellence in the interdisciplinary study of
cognition and computation in human communication. Drawing together
researchers from Edinburgh, Glasgow and Durham, HCRC focusses on the
psychological aspects of real language processing.
Facilities: Edinburgh contains the largest concentration of expertise
in Artificial Intelligence and Natural Language Processing in Europe.
Students have access to that expertise, to Edinburgh's large copyright
libraries, and within Cognitive Science, to a substantial offprint
library. The department possesses extensive computing facilities based
on a network of Sun workstations and Apple Macintoshes; access to
Edinburgh's concurrent supercomputer and other central computing
services is easily arranged.
Requirements: Applicants should normally have at least a good Second
Class Honours degree (or its equivalent) in one of the participating
areas or in an appropriate joint honours programme.
Funding: UK and EC students following the MSc and PhD courses are
eligible for ESRC, SERC studentships. Overseas candidates for
the PhD can apply for Edinburgh University Studentships and ORS awards,
though these are subject to strong competition.
Deadline for applications for 1992-1993: 1st March 1993.
If you would like more information about the Postgraduate Programme in
Cognitive Science at the University of Edinburgh, write to:
Director of Admissions
Centre for Cognitive Science
University of Edinburgh
2 Buccleuch Place
Edinburgh, EH8 9LW
Scotland.
Telephone: +44 31 650 4432
Fax: +44 31 650 4587
Email: info@cogsci.ed.ac.uk
******************************************************************************
------------------------------
Subject: Building energy predictor Competition - "The Great Energy Shootout"
From: "Dr. Jan F. Kreider, Director, Energy Center, U. of Colorado,Boulder, CO 80309-0428, USA; Phone\
303-492-7603" <JKREIDER@VAXF.COLORADO.EDU>
Date: 30 Dec 92 20:53:22 -0700
The following is the text of the rules for a data analysis competition
having to do with hourly building and weather data. We invite
those interested to request the data as described below. Andreas
Weigand and Mike Mozer are hereby thanked for their advice and help
with the rules and conduct of this competition.
"THE GREAT ENERGY PREDICTOR SHOOTOUT" - THE FIRST BUILDING DATA ANALYSIS AND
PREDICTION COMPETITION
Concept and Summary
ASHRAE Meeting
Denver, Colorado
June, 1993
Co-chaired by Jan F. Kreider and Jeff S. Haberl
Active Period: December 1, 1992 - April 30, 1993
INTRODUCTION
A wide range of new techniques is now being applied to the analysis problems
involved with predicting the future behavior of HVAC systems and deducing
properties of these systems. Similar problems arise in most observational
disciplines, including physics, biology, and economics. New tools, such as
genetic algorithms, simulated annealing, the use of connectionist models for
forecasting and tree-based classifiers or the extraction of parameters of
nonlinear systems with time-delay embedding, promise to provide results that
are unobtainable with more traditional techniques. Unfortunately, the
realization and evaluation of this promise has been hampered by the difficulty
of making rigorous comparisons between competing techniques, particularly ones
that come from different disciplines. The prediction of energy usage by HVAC
systems is important for purposes of HVAC diagnostics, system control,
optimization and energy management.
In order to facilitate such comparisons and to foster contact among the
relevant disciplines, ASHRAE's TC4.7 and TC 1.5 have organized a building data
analysis and prediction competition in the form of an ASHRAE seminar to be held
in Denver in June, 1993. Forecasting or prediction using empirical models will
be the goal of the competition. (Neither system characterization, system
identification nor simulation code validation [e.g., DOE-2 or BLAST] are the
subject of this seminar; they will be addressed in a future session.) Two
carefully chosen sets of energy and environmental data from real buildings
will be made available to the contestants. Each contestant will be required to
prepare quantitative analyses of these data and submit them to the seminar
co-chairs prior to the ASHRAE seminar. Those with the best results will be
asked to make a presentation to the seminar.
At the close of the competition the performance of the techniques submitted
will be compared and published. If there is sufficient interest, a server
accessible by modem may be set up to operate as an on-line archive of
interesting data sets, programs, and comparisons among algorithms in the
future. There will be no monetary prizes. An ASHRAE symposium has been
scheduled for the Winter 1994 ASHRAE meeting in New Orleans to explore the
results of the competition in formal papers.
The competition does not require advanced registration; to enter, simply
request the data (there is no charge for the data diskette) along with support
information and submit your analysis on time. The detailed description of the
competition and instructions for acquiring the data and entering the
competition are given below.
ACCESSING THE DATA
The data are available on disks (5.25-in size) in ASCII, IBM-PC format. To
receive the data, send a self-addressed 9 x 12 in. envelope, with a $2.90
priority mail stamp affixed, to:
Building Energy Predictor Shootout
Joint Center for Energy Management
Campus Box 428
University of Colorado
Boulder, CO 80309-0428
Instructions on submitting a return disk with the analysis of the data will be
included in a README file on the data disk. The disk will also include an
entry form that each entrant will need to complete and submit along with the
results.
FOR MORE INFORMATION
Further questions about the competition should be directed to either of the
organizers:
Professor Jan F. Kreider, Director Professor Jeff S. Haberl
Joint Center for Energy Management Department of Mechanical
Engineering
Campus Box 428 Texas A&M University
University of Colorado College Station, TX 77843-3123
Boulder, CO 80309-0428 Phone: 409-845-1560
Phone: 303-492-3915 Fax: 409-862-2762
Fax: 303-492-7317 E-mail: JSH4037@TAMSIGMA (Bitnet)
E-mail: JKREIDER@VAXF.COLORADO.EDU
Detailed instructions and data set descriptions are included in the attached
document.
[PB]
INSTRUCTIONS - "The Great Energy Predictor Shootout"
Contents
I. Philosophy
II. General Information
III. Acquiring and Submitting Data
IV. Data Sets
V. Submittals
VI. Other Matters
1.1 Philosophy
This competition has been organized to help clarify the conflicting claims
among many researchers who use and analyze building energy data and to foster
contact among these persons and their institutions. The intent is not
necessarily only to declare winners but rather to set up a format in which
rigorous evaluations of techniques can be made. Because there are natural
measures of performance, a rank-ordering will be given. In all cases, however,
the goal is to collect and analyze quantitative results in order to understand
similarities and differences among the approaches.
1.2 General Information
Overview
This section contains the instructions on how to participate in the
competition.
Data: Two distinct data sets are provided for prediction. Contestants will be
given these two sets of independent variables with the corresponding values of
dependent variables, e.g., energy usage. The accuracy of predictions of the
dependent variables from values of independent variables from this data set is
one of the criteria for judging this competition.
However, a more rigorous test is also planned. Some of the dependent variable
values will be withheld from each of the two data sets (this is explained in
detail in the next section). "Withheld" means that you will be provided with a
set of independent variables for which the corresponding values of dependent
variables have been withheld by the organizers
[NOTE "For example you might be given a testing set consisting of weather and oc
The data set from which the independent variables have been withheld are
hereinafter called the "testing set" whereas the data that include both
independent and dependent variable values are called the "training set."
Although this nomenclature is common in some numerical approaches and not in
others, it will provide an understandable nomenclature for this competition.
The independent variable values in the testing set will will be used by each
participant to make their best predictions of the corresponding dependent
variables. The organizers will compare these predictions by each contestant
with the true (data) values of the dependent variables that are known only to
the organizers. This second aspect of the competition is expected to be of
considerable interest to the seminar audience.
Entries: The competition will start on December 1, 1992 and will end on April
30,1993. Entries received after that date cannot be considered. The format for
the entries, described in the following sections and in the entry form supplied
on the data diskette must be followed exactly, or the entry will regretfully
have to be rejected.
Results: Following the close of the competition, the results will be analyzed
and published. This will be in the form of the ASHRAE seminar (Denver, June,
1993) as described above. The seminar co-chairs will not participate in the
competition and but will be the sole analysts of the results. The overall
results will be presented at the seminar by the co-chairs followed by a
presentation by each participant on their methodology.
The results to be produced by the competitors are in the form of predictions
of the dependent variables for the two testing sets of independent variables.
These predictions will be submitted to the organizers who will evaluate them
using the same methods for all submissions. Competitors will also conduct a
self analysis of the accuracy of their prediction approach when applied to the
training set.
The following criteria will be used by the organizers for assessing the
respective accuracies of the entries when analyzing the testing set
Coefficient of Variation ,CV:
[EQN "CV == [Root [Sigma below [i=1] above n (y sub [pred,i] - y sub [dat
Mean Bias Error, MBE:
[EQN "MBE == [ [Sigma below [i=1] above n (y sub [pred,i] - y sub [data,i
where
[EQN "y sub [data,i]"] is a data value of the dependent variable
corresponding to a particular set of values of the independent variables.
[EQN "y sub [pred,i] "] is a predicted dependent variable value for the
same set of independent variables above; these values are predictions by
the entrants.
[EQN "y bar sub data"] is the mean value of the dependent variable
testing data set
[EQN "n"] is the number of sets of data in the testing set
Other statistics such as the correlation coefficient and maximum error may also
be reported in a brief written summary assembled by the seminar co-chairs. Time
permitting, graphical comparisons will be also prepared by the organizers.
During each entrant's seminar presentation they may use any presentation of
scientific value that they wish on the performance of their methods on the
training set.
Prizes: There are no prizes in the competition (to prevent unnecessary
disagreements).
Secrecy: Because this is an open scientific study, entries that provide
results without describing the methods used are not acceptable. On the other
hand we recognize that a great deal of labor might have been applied to develop
commercially useful applications and full details of those need not be
revealed. Sufficient information has to be supplied so that the results can in
principle be independently verified. It is not necessary to submit practical
implementation details or the computer code. However, we encourage sharing the
software at the end of the competition. At a minimum, each participant should
supply a flow chart of their methodology and the data plots described below.
Future Plans: If interest warrants, it is planned that a computer server will
operate after the close of the competition as a central repository of
interesting data, analysis programs, and the results of other comparative
studies.
1.3 Acquiring and Submitting Data
This section describes how to retrieve the data sets for the competition and
how to submit competition entries.
The steps are: (1) read this section, (2) acquire the data, (3) analyze the
data, and (4) send in your results in along with an entry form.
The data are available on disks (5.25-in size) in ASCII, IBM-PC format. To
receive the data and other information, send a self-addressed 9 x 12 in.
envelope with a $2.90 priority mail stamp affixed to:
Building Energy Predictor Shootout
Joint Center for Energy Management
Campus Box 428
University of Colorado
Boulder, CO 80309-0428
Instructions on submitting a return disk with the analysis of the data will be
included in a README file on the data disk. The mailing will also include an
entry form that each entrant will need to complete out and submit along with
the results.
Completed entries (diskette with results plus completed entry form) should be
mailed to: Energy Shootout Entry Disks at the above address. Part of the entry
form will include your name and address and describe the machine type and
density that your submittal disks were prepared with. The disks (either 3.5-in
or 5.25-in. size of any density) must be in ASCII format readable by an MS-DOS
machine. Hard copy or nonconforming entries cannot be accepted.
1.4 Data Sets
There are two data sets provided; they are DOS-readable ASCII text files. The
data sets have been chosen to address two different sorts of building-related
data analysis problems. In this section we describe the general features of the
data sets.
A.dat (approximately 3,000 points)
This is a time record of hourly chilled water, hot water and whole building
electricity usage for a four-month period in an institutional building.
Weather data and a time stamp are also included. The hourly values of usage of
these three energy forms is to be predicted for the two following months. The
testing set consists of the two months following the four-month period.
B.dat (approximately 2,400 points)
These data consist of solar radiation measurements made by four fixed devices
to be used to predict the time-varying hourly beam radiation during a six-month
period. This four-pyranometer device is used in an adaptive controller to
predict building cooling loads. A random sample of data from the full data set
has been reserved as the training set of 1500 points. The value of beam
radiation is to be predicted from data from four fixed sensors for the testing
set of 900 additional points.
1.5 Submittals
The prediction tasks differ between the data sets (the sets were chosen to
emphasize different prediction problems). The withheld testing data used for
evaluating the predictions after the close of the competition will not be
available to any of the entrants.
A.dat
For data set A submit predictions (i.e., forecasts) for chilled water, hot
water and whole building electricity use for the two months following the
four-month training set. The testing set will include values of the same
independent variables (weather, date and time) as the training set. Submit
your predictions of the three energy end uses in serial order by appending
three columns containing your predictions to the right of the testing set
columns provided on the disk data file. You will therefore submit to the
organizers the testing set plus three columns containing your predictions. A
sample of how you are to submit your data will be supplied with the data
diskette.
The organizers will compare your predictions to the known values of the three
energy uses and report CV and MBE.
You are also to prepare and submit with your diskette several graphs for the
four-month training set data as shown in Figs. 1 and 2. Figure 1 is a time
series plot of actual data and a prediction along with the difference between
the two (Fig. 1 is such a plot for one month; you can either prepare one such
plot for each of the four months or just one plot for all four months; you
will need to prepare at least on such plot for each of the three energy end
uses). Figure 2 is a plot of hourly energy use vs. dry bulb temperature. Data
for all four months should be presented on one such graph for each of the three
energy end uses (total of three plots will be prepared, one each for chilled
water, hot water and whole building electricity). On each graph show the
values of CV and MBE as defined above.
Summary: You will submit to the seminar organizers one file on diskette with
your predictions of the three energy end uses for the testing set. You will
also submit several graphs, just described, representing the accuracy of your
prediction tool when used on the training set only.
B.dat
For data set B submit predictions for hourly beam radiation given four values
of hourly fixed-sensor insolation for the testing set that has been randomly
selected from the full data set. The testing set will include the values of
the same four independent variables (hourly insolation on four fixed surfaces)
as the training set. Submit your predictions of beam insolation in order by
appending one column containing their values to the right of the four testing
set columns provided on the disk data file. You will therefore submit to the
organizers the testing set plus one column containing your predictions. A
sample of how you are to submit your data will be supplied with the data
diskette.
The organizers will compare your predictions to the known values of the beam
radiation in the testing set and report CV and MBE.
You are also to prepare and submit with your diskette one graph (often called a
"scatterplot" or "crossplot") for the training set data as shown by the example
in Fig. 3. Figure 3 is a plot of actual data (abscissa) and prediction
(ordinate). You should prepare one such plot that includes all data in the
training set. On this graph show the value of CV and MBE as defined above.
Summary: You will submit to the seminar organizers one file on diskette with
your predictions for the testing set. You will also submit a graph, just
described, that represents the accuracy of your prediction tool when used on
the training set only.
Questions about these instructions should be addressed to either of the
organizers listed above.
1.6 Deadline and extensions
The competition ends at midnight on April 30, 1993; to be fair, we cannot
accept entries after this time. We will allow two weeks after this deadline
(until May 15th) for only the following two exceptions:
* Because of computer difficulty you were unable to submit the data in
time. Send the data before May 15th, along with an explanation of the
difficulty. The organizers must be notified of your need to have this
extension by April 30, 1993
* You just found out about the competition or just received the data.
Submit your entry before May 15th, along with an explanation why this
extension is needed.
[PB]
[WS 3.5 in]
Figure 1. Example time series plot showing data, prediction and difference
between the two. For the competition submittal also affix the values of CV and
MBE to each graph.
[WS 3.5 in]
Figure 2. Example plot showing energy consumption (here steam) plotted vs dry
bulb temperature. For the competition submittal also affix the values of CV
and MBE to each graph.
[PB]
[WS 4 in]
Figure 3. Example scatterplot showing data and prediction crossplotted. For
the competition submittal also affix the values of CV and MBE to each graph.
[SHOOTOUT.DOC]
[PB]
[WS 1 in]
M E M O R A N D U M
TO: Building Analyst Colleague
FROM: Jan F. Kreider
SUBJECT: Building Energy Predictor Shootout
DATE: November 16, 1992
In order to facilitate comparisons among the many empirical techniques used to
predict building demand and energy use and to foster contact among the
relevant disciplines, ASHRAE's TC 4.7 and TC 1.5 have organized a building
data analysis and prediction competition in the form of an ASHRAE seminar to
be held in Denver in June, 1993. Forecasting or prediction using empirical
models will be the goal of the competition.
Jeff Haberl and I invite you to participate. The attached summary explains how
you can enter this friendly, no-cost competition. You have received this
mailing because of the known interest of yourself and your colleagues in this
area of building science research. The enclosure should be self explanatory
but donot hesitate to call me at the number above if you have questions. Good
luck!
Enclosure
[SHOOTOUT.DOC]
For example you might be given a testing set consisting of weather and occupancy data (the independent variables) along with chilled
water use (the dependent variable) for a four-month period. For the fifth month you would only be given the weather and
occupancy data but would be asked to predict the chilled water use based on the capability of your method developed with the four mo
nths of training data.
/
------------------------------
End of Neuron Digest [Volume 11 Issue 2]
****************************************
