Engineering

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ECMM124 - Hydroinformatics Tools (2015)

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MODULE TITLEHydroinformatics Tools CREDIT VALUE15
MODULE CODEECMM124 MODULE CONVENERProf Dragan Savic FREng (Coordinator)
DURATION: TERM 1 2 3
DURATION: WEEKS 11 weeks 11 weeks 0
Number of Students Taking Module (anticipated) 23
DESCRIPTION - summary of the module content

The efficient use of water for different purposes is presenting a number of different problems. The emerging field of hydroinformatics is designed to address these, using information and communications technologies.

 
On this module, you will look into water systems, including water supply, flooding, risk assessment and computations. Furthermore, you will learn about simulation and optimisation models and apply them to practical problems, including water supply and flood management and prevention. 
 

AIMS - intentions of the module

This module aims to give you a basic understanding of tools in the emerging field of hydroinformatics for the practising engineer. It also offers practical experience in using these tools within the water management context.

 

This module covers Specific Learning Outcomes in Engineering, which apply to accredited programmes at Bachelors/MEng/Masters level. These contribute to the  educational requirements for CEng registration (as defined under the UK Standard for Professional Engineering Competence – UK-SPEC).
 
 
 
This module correlates to references MU1 - MU3, ME1 - ME3, MD2, MP1, GM1, GM2 and GM4. These references are indices of the specific learning outcomes expected of Bachelors/MEng/Masters candidates set out in UK-SPEC, codified with reference to systems used by professional accrediting institutions. A full list of the standards can be found on the Engineering Council's website, at http://www.engc.org.uk

 

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module, you should be able to:

 

Module Specific Skills and Knowledge:
1 understand the systems analysis approach to modelling of water systems;
2 comprehend a number of hydroinformatics methods and tools;
3 critically appraise the use of hydroinformatics methods and tools for a variety of water management problems.
Discipline Specific Skills and Knowledge:
4 identify suitable methods and tools for water problem solving;
5 critically assess research results;
6 evidence some practical experience of using hydroinformatics methods and tools.
Personal and Key Transferable/ Employment Skills and  Knowledge:
7 show enhanced independent learning;
8 demonstrate strong report and presentation skills;
9 reveal improved skills in using computer software.

SYLLABUS PLAN - summary of the structure and academic content of the module

- systems approach to water management, simulation and optimisation methodologies, multicriteria decision making;

- classical and intelligent optimisation strategies – linear programming, modern heuristic methods, including evolutionary computing, simulated annealing, shuffled complex algorithm, particle swarm optimisation, ant colony systems;

- data mining methods, predictive data mining, knowledge discovery, rule-based methods, artificial neural networks, genetic programming, fuzzy sets;

- decision support systems (DSS), , software tools, water management DSS;

- complexity - cellular automata and grid-based methods;

- modelling and models, typology, scale, forward and inverse modelling, calibration, validation and verification;

- application examples in water management: calibration and validation, data mining, non-linear regression, pattern recognition, forecasting, decision support.
 

LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 40.00 Guided Independent Study 110.00 Placement / Study Abroad
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled learning activities 40 Lectures and tutorials
Guided independent study 110 Assessment preparation; private study
     

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Questions posed and answered in the class Various durations All Verbal (in class)
       
       
       
       

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 40 Written Exams 60 Practical Exams
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Written exam 60 2 hours All Written (on request)
Assignment on practical application of hydroinformatics tools 20 1,000-1,500 words, including graphs and tables All Written
Report on a given topic 20 1,000 - 1,500 equivalent words, including graphs and tables All Written
         
         

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-reassessment
All above Written exam (100%) All August Ref/Def period
       
       

 

RE-ASSESSMENT NOTES

If a module is normally assessed entirely by coursework, all referred/deferred assessments will normally be by assignment.

If a module is normally assessed by examination or examination plus coursework, referred and deferred assessment will normally be by examination. For referrals, only the examination will count, a mark of 50% being awarded if the examination is passed. For deferrals, candidates will be awarded the higher of the deferred examination mark or the deferred examination mark combined with the original coursework mark.

RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

ELE: http://vle.exeter.ac.uk

Reading list for this module:

Type Author Title Edition Publisher Year ISBN Search
Set Banzhaf W, Nordin P, Keller R E and Francone F D Genetic Programming: an introduction Morgan Kaufmann 1998 978-1558605107 [Library]
Set Haykin, S Neural Networks: A Comprehensive Foundation 2nd Pearson 1999 000-013-908-385-3 [Library]
Set Michaelewicz, Z Genetic Algorithms + Data Structures = Evolution Programmes 3rd Springer-Verlag 1996 000-354-055-387-8 [Library]
Set Pyle D Data Preparation for Data Mining Morgan Kaufmann 1999 978-1558605299 [Library]
Set Ross T J Fuzzy Logic with Engineering Applications 2nd John Wiley 2004 978-0470860755 [Library]
CREDIT VALUE 15 ECTS VALUE 7.5
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Friday 09 January 2015 LAST REVISION DATE Wednesday 25 November 2015
KEY WORDS SEARCH Hydroinformatics; optimisation; modelling; machine learning; neural networks; genetic algorithms; cellular automata.