Minimizing pricing policies based on user load profiles and residential demand responses in smart grids

This paper considers the time of use (TOU) pricing scheme to propose a consumer aware pricing policy (CAPP), where each customer receives a separate electricity pricing signal. These pricing signals are obtained based on individualized load demand patterns to optimally manage the flexible load demand. The main objective of CAPP is to reduce the...

Computational Discovery of Transaction-Based Financial Crime via Grammatical Evolution: The Case of Ponzi Schemes

The financial sector continues to experience wide digitalization; the resulting transactional activity creates large amounts of data, in principle enabling public and private actors to better understand the social domain they operate on, possibly facilitating the design of interventions to reduce illegal activity. However, the adversarial nature...

Portfolio Optimisation Using the D-Wave Quantum Annealer

Shrinking Bouma's window: How to model crowding in dense displays

In crowding, perception of a target deteriorates in the presence of nearby flankers. Traditionally, it is thought that visual crowding obeys Bouma's law, i.e., all elements within a certain distance interfere with the target, and that adding more elements always leads to stronger crowding. Crowding is predominantly studied using sparse displays ...

Challenges in heat network design optimization

Different stakeholders have different design considerations that shape a heating grid. In short term, theserange from achieving lowest ownership costs to preventing monopolies. In long term, project developersfocus on how uncertainties of design parameters (e.g. demand/supply, heat prices) affect the grid designand, ultimately, the business case...

Long-term memory-induced synchronisation can impair collective performance in congested systems

We investigate the hypothesis that long-term memory in populations of agents can lead to counterproductive emergent properties at the system level. Our investigation is framed in the context of a discrete, one-dimensional road-traffic congestion model: we investigate the influence of simple cognition in a population of rational commuter agents...

Automated daily maintenance planning for offshore wind farms

Offshore wind farm managers and schedulers need to manage large numbers of wind turbine visits every day, in order to: repair minor faults; conduct inspections; and perform scheduled service operations. Daily schedules form a choice of which maintenance activities to conduct, taking account of: constraints on weather conditions, shifts, vessel...

Mapping of synchronous dataflow graphs on MPSoCs based on parallelism enhancement

Multi-processor systems-on-chips are widely adopted in implementing modern streaming applications to satisfy the ever increasing computation requirements. To take advantage of this kind of platform, it is necessary to map tasks of the application properly to different processors, so as to fully exploit the inherent task-level parallelism and...

Measurement network design including traveltime determinations to minimize model prediction uncertainty

Traveltime determinations have found increasing application in the characterization of groundwater systems. No algorithms are available, however, to optimally design sampling strategies including this information type. We propose a first-order methodology to include groundwater age or tracer arrival time determinations in measurement network...

Genetic algorithm based two-mode clustering of metabolomics data

Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering methods allow for analysis of the behavior of...

Inversion for bottom parameters using low frequency reverberation data

Active sonar reverberation returns offer the possibility to invert for geo-acoustic bottom parameters to characterise the underwater environment. We present the results of synthetic inversions of reverberation returs generated with a ray-based reverberation model in which bottom scattering is modelled according to a modified Lambert's rule. The...

A case study of a multiobjective recombinative genetic algorithm with coevolutionary sharing

We present a multiobjective genetic algorithm that incorporates various genetic algorithm techniques that have been proven to be efficient and robust in their problem domain. More specifically, we integrate rank based selection, adaptive niching through coevolutionary sharing, elitist recombination, and non-dominated sorting into a...

A Case Study of a Multiobjective Elitist Recombinative Genetic Algorithm with Coevolutionary Sharing

We present a multiobjective genetic algorithm that incorporates various genetic algorithm techniques that have been proven to be efficient and robust in their problem domain. More specifically, we integrate rank based selection, adaptive niching through coevolutionary sharing, elitist recombination, and non-dominated sorting into a...

Underwater Target Localization and Estimation of Ocean Environmental Parameters Using a Genetic Algorithm

In the field of underwater acoustics the signal processing technique " Matched Field

Edificio project: A neuro-fuzzy approach to building energy management systems

It is well known that building installations for indoor climate control, consume a substantial part of the total energy consumption and that at present these installations use much more energy than required due to inadequate settings and poor control and management strategies. European building energy management is diffuse since design,...

Genetic contour matching

Object recognition can be formulated as an optimization problem. The objective function measures for instance the evidential support for any particular projection of the parameterized object contour model onto the input image. A genetic algorithm can be used to find a set of parameters which provide an optimal interpretation of the image in...