Electrical power grid network optimisation by evolutionary computing

A major factor in the consideration of an electrical power network of the scale of a national grid is the calculation of power flow and in particular, optimal power flow. This paper considers such a network, in which distributed generation is used, and examines how the network can be optimized, in terms of transmission line capacity, in order to obtain optimal or at least high-performing configurations, using multi-objective optimisation by evolutionary computing methods

Clutter Reduction in Parallel Coordinates using Binning Approach for Improved Visualization

As the data and number of information sources keeps on mounting, the mining of necessary information and their presentation in a human delicate form becomes a great challenge. Visualization helps us to pictorially represent, evaluate and uncover the knowledge from the data under consideration. Data visualization offers its immense opportunity in the fields of trade, banking, finance, insurance, energy etc. With the data explosion in various fields, there is a large importance for visualization techniques. But when the quantity of data becomes elevated, the visualization methods may take away the competency. Parallel coordinates is an eminent and often used method for data visualization. However the efficiency of this method will be abridged if there are large amount of instances in the dataset, thereby making the visualization clumsier and the data retrieval very inefficient. Here we introduced a data summarization approach as a preprocessing step to the existing parallel coordinate method to make the visualization more proficient

Pixel-Based Parallel-Coordinates Technique For Outlier Detection In Cardiac Patient Dataset.

Visual Exploration technique applies human visual perception to explore large data sets and have proven to be of high value in exploratory data analysis. Pixel-based visual exploration relies on basic features that human perceptual system inherently assimilates very quickly: color size and shape

Quantitative Approach on Parallel Coordinates and Scatter Plots for Multidimensional-Data Visual Analytics

Parallel coordinates and scatter plots are two well-known visualization techniques for multidimensional data analytics and often employed cooperatively for flexibility increase in exploration of such data. Existing approaches approximately consider qualitative issues and single attribute comparison, which might face statistic challenges in case of quantitative requirement. This paper introduces a new quantitative approach for visual enhancement of parallel coordinates and scatter plots in term of multiple attribute comparison. The method is based on the visual integration of interactive stacked bars and visual queries on parallel axes and scatter charts. The parallel coordinates play the role of a context view while the scatter charts are for focus details. Using the technique, users could not only quantitatively analyze multivariate data, but also flexibly compare multiple target attributes. Moreover, further investigation is enabled for deep understanding of desired information. The characteristics and usefulness of our approach are demonstrated via a case study with two typical use cases

Blending aggregation and selection: Adapting parallel coordinates for the visualization of large datasets

Many of the traditional data visualization techniques, which proved to be supportive for exploratory analysis of datasets of moderate sizes, fail to fulfil their function when applied to large datasets. There are two approaches to coping with large amounts of data: data selection, when only a portion of data is displayed, and data aggregation, i.e. grouping data items and considering the groups instead of the original data. None of these approaches alone suits the needs of exploratory data analysis, which requires consideration of data on all levels: overall (considering a dataset as a whole), intermediate (viewing and comparing collective characteristics of arbitrary data subsets, or classes), and elementary (accessing individual data items). Therefore, it is necessary to combine these approaches, i.e. build a tool showing the whole set and arbitrarily defined subsets (object classes) in an aggregated way and superimposing this with a representation of arbitrarily selected individual data items. We have achieved such a combination of approaches by modifying the technique of parallel coordinate plot. These modifications are described and analysed in the paper

WINVR09-701 VIRTUAL PROTOTYPING BY USING HOLOGRAPHIC DISPLAYS -BUT WHAT ABOUT LARGE DATA PROBLEMS?

ABSTRACT The work reported in this paper is part of the research that explores the viability of using holographic displays as part of virtual prototyping package of supporting tools. The focus is principally on handling of large data problems, which are among the common problems of most volumetric displays. The paper first reviews related works. After describing the large data related problems that designers might face in using holographic displays and identifying the conceptual design tasks that could be supported by using these displays, a concept for handling the large data problems through elimination of irrelevant image details is introduced. An application example showing how some elements of the proposed concept function in the real world is also presented. The main contributions of this work can be summarized as follows: (i) we have demonstrated that through simplifications, visual abstractions, data clustering or other generalization methods, less complicated holographic images that require less computing resources but yet suitable 3D for some conceptual design tasks or virtual prototyping can be created; and (ii) we have defined the steps of a scalable highlevel algorithm, that can be expanded or tuned to suit visualization demands in various conceptual design tasks. In the ongoing work, we aim to develop built in procedures within the proposed algorithm that would reduce the amount of image details without significantly affecting the appropriateness of the overall virtual model. And because of the reduced image details, it would be possible to display less complicated 3D virtual objects and in this way computing resources could be saved. KEYWORDS 3D product visualization, virtual prototyping, volumetric displays, computer-aided virtual design, conceptual design

Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Visualisointitekniikat käyttäjän vertailutilanteen apuna

Visualisointitekniikoita on tutkittu paljon, mutta yleensä tutkimuksissa keskitytään vain tekniikoiden teknisiin ominaisuuksiin. Tämän työn tavoitteena on tarkastella, kuinka eri visualisointitekniikat tukevat käyttäjää hänen konkreettisessa valintatilanteessaan. Vertailutyökaluna käytetään realistista autonvalintatilannetta, jonka ratkaisemisessa hyödynnetään visualisointeja. Käytettävyystestien avulla selvitetään, mitä hyötyjä ja ongelmia tutkittavien visualisointitekniikoiden käytössä ilmenee ja onko tehtävien suorittaminen jollakin tekniikalla helpompaa tai vaikeampaa kuin toisella. Lisäksi tutkitaan, millaisia käytettävyysongelmia tekniikoissa on, ja onko esille tulleet ongelmat mahdollisesti onnistuttu kiertämään jossain toisessa tutkittavassa tekniikassa. Testien perusteella yksikään tutkittu visualisointitekniikka ei tukenut käyttäjän valintatilannetta ongelmattomasti. Testitulosten pohjalta laaditulla merkkipohjaisen taulukkomuodon ja pylväsdiagrammien yhdistelmällä visualisointitekniikoita vaivanneet ongelmat olisivat kuitenkin mahdollisesti ratkaistavissa