Social Network Community Detection for DMA Creation: Criteria Analysis through Multilevel Optimization

Brentan, Bruno Melo; Campbell, Enrique; Lima, Gustavo Meirelles; Luvizotto, Edevar; Izquierdo, Joaquín

doi:10.1155/2017/9053238

Cited by 42 publications

(32 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…They are usually related to economic feasibility [40][41][42] or the preservation of the hydraulic reliability of the WDN [11,17]; other aspects such as pressure uniformity and water quality issues are also included. In contrast to Ferrari et al [21] and Brentan et al [43], we try not to make the original flow velocity deteriorate, especially for pipes that originally had a low flow velocity. More attention can be paid to better execute pressure management [44] or more quickly detect and control accidental events (e.g., pipe bursts and water contamination) in future research.…”

Section: Discussionmentioning

confidence: 99%

An Improved Genetic Algorithm for Optimal Layout of Flow Meters and Valves in Water Network Partitioning

Shao

Yao

Zhang

et al. 2019

Water

View full text Add to dashboard Cite

The paradigm of “divide and conquer” has been well used in Water Distribution Systems (WDSs) zoning planning in recent years. Indeed, Water Network Partitioning (WNP) has played an irreplaceable role in leakage control and pressure management; meanwhile it also has certain drawbacks, such as reduction of the supply reliability of the pipe network system and increased terminal dead water, as a result of the closure of the pipe section. In this paper, an improvement is made to the method proposed by Di Nardo et al. (2013) for optimal location of flow meters and valves. Three improvements to the genetic algorithm are proposed in this work for better and faster optimization in the dividing phase of WNP: preliminary hydraulic analysis which reduces the number of decision variables; modifications to the crossover mechanism to protect the superior individuals in the later stage; and boundary pipe grouping and mutation based on the pipe importance. The objective function considers the master–subordinate relationship when minimizing the number of flow meters and the difference of hydraulic state compared to original WDS. Another objective function of minimizing the deterioration of water quality compared to original WDS is also evaluated. The proposed method is applied for the WNP in a real WDS. Results show that it plays an effective role in the optimization of layout of the flow meters and valves in WNP.

show abstract

Section: Discussionmentioning

confidence: 99%

An Improved Genetic Algorithm for Optimal Layout of Flow Meters and Valves in Water Network Partitioning

Shao

Yao

Zhang

et al. 2019

Water

View full text Add to dashboard Cite

show abstract

“…Sometimes, prior expert knowledge can be introduced in the form of rules (Gibert et al, 2010b) or ontologies (Gibert et al, 2014) to introduce semantic information into the process, and get classes easier to interpret. Graph theory (Herrera et al, 2015;di Nardo et al, 2018) and social network theory (Campbell et al, 2016;Brentan et al, 2017aBrentan et al, , 2018a have also found applications in clustering. Density-based methods, like DBScan (Ester et al, 1996) or OPTICS (Ankerst et al, 1999) are computation-based methods detecting areas with higher concentration of objects and work well with non-globular clusters.…”

Section: Profiling Dm Methods: Clustering and Density Estimationmentioning

confidence: 99%

“…A hybrid combination SOM+k-Means Clustering was used to improve planning, operation and management of Water Distribution Systems in Brentan et al (2018b), which can be easily extended to other environmental problems, etc. Graph theory (Herrera et al, 2015;di Nardo et al, 2018) and social network theory (Campbell et al, 2016;Brentan et al, 2017aBrentan et al, ,2018a have been used to cluster a water distribution network into sectors so as to optimize these infrastructures' management. In Blanco et al (2018) SCADA data is used to identify health profiles of wind turbines.…”

Section: Applications and Referencesmentioning

confidence: 99%

Which method to use? An assessment of data mining methods in Environmental Data Science

Gibert

Izquierdo

Sànchez–Marrè

et al. 2018

Environmental Modelling & Software

Self Cite

View full text Add to dashboard Cite

Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reasoning or Bayesian networks have been applied in environmental modelling, while other methods, like support vector machines among others, have yet to be taken up on a wide scale. There is greater scope for many lesser known techniques to be applied in environmental research, with the potential to contribute to addressing some of the current open environmental challenges. However, selecting the best DM technique for a given environmental problem is not a simple decision, and there is a lack of guidelines and criteria that helps the data scientist and environmental scientists to ensure effective knowledge extraction from data. This paper provides a broad introduction to the use of DM in Data Science processes for environmental researchers. Data Science contains three main steps (pre-processing, data mining and post-processing). This paper provides a conceptualization of Environmental Systems and a conceptualization of DM methods, which are in the core step of the Data Science process. These two elements define a conceptual framework that is on the basis of a new methodology proposed for relating the characteristics of a given environmental problem with a family of Data Mining methods. The paper provides a general overview and guidelines of DM techniques to a non-expert user, who can decide with this support which is the more suitable technique to solve their problem at hand. The decision is related to the bidimensional relationship between the type of environmental system and the type of DM method. An illustrative two way table containing references for each pair Environmental System-Data Mining method is presented and discussed. Some examples of how the proposed methodology is used to support DM method selection are also presented, and challenges and future trends are identified.

show abstract

“…In this situation, a clever solution is to give each geodesic equal weight such that the weights add to unity [12,[26][27][28]. Newman [4] put forward another method assuming that the route of information spreading through is some kind of random walk.…”

Section: Optimal Route Between Nonadjacentmentioning

confidence: 99%

Quasi‐Closeness: A Toolkit for Social Network Applications Involving Indirect Connections

Yin

Liu

2017

Mathematical Problems in Engineering

View full text Add to dashboard Cite

We come up with a punishment in the form of exponential decay for the number of vertices that a path passes through, which is able to reconcile the contradictory effects of geodesic length and edge weights. This core thought is the key to handling three typical applications; that is, given an information demander, he may be faced with the following problems: choosing optimal route to contact the single supplier, picking out the best supplier between multiple candidates, and calculating his point centrality, which involves indirect connections. Accordingly, three concrete solutions in one logic thread are proposed. Firstly, by adding a constraint to Dijkstra algorithm, we limit our candidates for optimal route to the sample space of geodesics. Secondly, we come up with a unified standard for the comparison between adjacent and nonadjacent vertices. Through punishment in the form of exponential decay, the attenuation effect caused by the number of vertices that a path passes through has been offset. Then the adjacent vertices and punished nonadjacent vertices can be compared directly. At last, an unprecedented centrality index, quasi-closeness, is ready to come out, with direct and indirect connections being summed up.

show abstract

Social Network Community Detection for DMA Creation: Criteria Analysis through Multilevel Optimization

Cited by 42 publications

References 38 publications

An Improved Genetic Algorithm for Optimal Layout of Flow Meters and Valves in Water Network Partitioning

An Improved Genetic Algorithm for Optimal Layout of Flow Meters and Valves in Water Network Partitioning

Which method to use? An assessment of data mining methods in Environmental Data Science

Quasi‐Closeness: A Toolkit for Social Network Applications Involving Indirect Connections

Contact Info

Product

Resources

About