New approaches of particle swarm optimisation algorithm based on Gaussian and Cauchy distributions to adjust the control points of B-spline neural networks are proposed. B-spline networks are trained by gradient-based methods, which may fall into local minimum during the learning procedure. To overcome the problems encountered by the conventional learning methods, particle swarm optimisation  ...

This paper proposes a method for designing EMC shielding enclosures using a peer-to-peer based distributed optimisation system based on a modified particle swarm optimisation (PSO) algorithm. This optimisation system is used to efficiently obtain optimal solutions to a shielding enclosure design problem by sampling only a small fraction of the total problem space. Such a system would find use i...

This paper considers a residential market with real-time electricity pricing and flexible electricity consumption profiles for customers. Such a market raises an optimisation problem for home automation systems where they need to schedule consumption activities to reduce costs, whilst maintaining a base level of comfort and convenience. This optimisation problem faces uncertainty in real-time p...

Evolutionary algorithms are well established methods for shape and design optimisations and they are applied to a large variety of problems. Especially for the optimisation of aerodynamic properties various publications demonstrate the potential of the method. Two major problems in the application of evolutionary optimisation methods for the improvement of aerodynamic properties are the represe...

In robot odometry and SLAM applications the real trajectory is estimated incrementally. This produces an accumulation of errors which gives raise to a drift in the trajectory. When revisiting a previous position this drift becomes observable and thus it can be corrected by applying loop closing techniques. Ultimately a loop closing process leads to an optimisation problem where new constraints ...

In biomechanics, musculoskeletal models are typically redundant. This situation is referred to as the distribution problem. Often, static, non-linear optimisation methods of the form "min: phi(f) subject to mechanical and muscular constraints" have been used to extract a unique set of muscle forces. Here, we present a method for validating this class of non-linear optimisation approaches where ...

the purpose of this study was to examine serum selenium (se), lipoproteins and testosterone responses to a single session of circuit resistance exercise. fourteen male college students volunteered in the present study. blood samples were taken at 30minutes before, immediately after 25 and 60minutes of single session of circuit resistance exercise (10 exercise, 20s for each exercise, and at 60%1...

Membrane computing models (also known as P Systems) that solve optimisation problems using genetic algorithms, ant colony optimisation, quantum-inspired evolutionary algorithm and particle swarm optimisation have been defined and are efficiently used in several applications. This paper describes the design of a variant of the existing Distributed P system (dP system) that is augmented with new ...

Since the establishment of the area of search-based software engineering, a wide range of optimisation techniques have been applied to automate various stages of software design and development. Architecture optimisation is one of the aspects that has been automated with methods like genetic algorithms, local search, and ant colony optimisation. A key challenge with all of these approaches is t...

We present a model hierarchy multilevel optimisation approach to solve an optimal boundary control problem in glass manufacturing. The process is modelled by radiative heat transfer and formulated as an optimal control problem restricted by partial differential algebraic equations (PDAE) and additional control constraints. We consider a sequence of model approximations given by space-time depen...