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Showing 1 to 19 of 19 for “"Particle swarm optimisation (PSO)"”.
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Exergy Based SI Engine Model Optimisation. Exergy Based Simulation and Modelling of Bi-fuel SI Engine for Optimisation of Equivalence Ratio and Ignition Time Using Artificial Neural Network (ANN) Emulation and Particle Swarm Optimisation (PSO).
In this thesis, exergy based SI engine model optimisation (EBSIEMO) is studied and evaluated. A four-stroke bi-fuel spark ignition (SI) engine is modelled for optimisation of engine performance based upon exergy analysis. An artificial neural network (ANN) is used as an emulator to speed up the …
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Multi-objective optimisation using sharing in swarm optimisation algorithms
… with the help of evolutionary computation. Particle Swarm Optimisation (PSO) is a relatively new heuristic that shares some similarities with evolutionary computation techniques, and that recently has been successfully modified to solve multi-objective optimisation problems. In this thesis …
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Design and modelling of beam steering antenna array for mobile and wireless applications using optimisation algorithms. Simulation and measrement of switch and phase shifter for beam steering antenna array by applying reactive loading and time modulated switching techniques, optimised using genetic algorithms and particle swarm methods.
… using the genetic algorithm (GA) and particle swarm optimisation (PSO) techniques as optimisation design tools. Several antenna designs were implemented and tested: initially, a printed dipole antenna integrated with a duplex RF switch used for mobile base station antenna beam steering …
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Advanced computational techniques for pipe burst detection and localisation in water distribution networks
… a comparative analysis of hyperparameter optimisation techniques, Particle Swarm Optimisation (PSO) and Population-Based Training (PBT), for FL-DL architectures. This investigation addresses the limitations of traditional detection methods, which are often costly, labour-intensive, and …
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Self-limitation, dynamic and flexible approaches for particle swarm optimisation
Swarm Intelligence (SI) is one of the prominent techniques employed to solve optimisation problems. It has been applied to problems pertaining to engineering, schedule, planning, networking and design. However, this technique has two main limitations. First, the SI technique may not be suitable for …
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An intelligent manufacturing system for heat treatment scheduling
… scheduling, a furnace model is developed for optimisation proposes. Furthermore, a system that is capable of selecting the optimal heat treatment regime is developed so the required metal properties can be achieved with the least energy consumption and the shortest time using Neuro-Fuzzy (NF) …
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Baldwinian-based meta-heuristic for robust engineering optimisation
… research was to identify problems in engineering optimisation and then to develop novel solutions to the identified problems. First, principles of computational optimisation were studied and a literature review was conducted. It emerged that the latest research in the area of automated engineering …
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State switching in multi-stable systems: control and optimisation.
… simulation on the test systems. Moreover, optimisation of the controller (based on multiple performance objectives) can further improve system performance. Two performance objectives - maximum peak of control input and switching duration - are adopted in optimising the proposed PD-like …
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Network-level maintenance decisions for flexible pavement using a soft computing-based framework
… classification; performance prediction; and optimisation for decision-making. For section classification, this research presents a fuzzy inference system (FIS), with appropriate membership functions for section classifications and for calculating the pavement condition index (PCI). The …
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An Evaluation of Performance Enhancements to Particle Swarm Optimisation on Real-World Data
Swarm Computation is a relatively new optimisation paradigm. The basic premise is to model the collective behaviour of self-organised natural phenomena such as swarms, flocks and shoals, in order to solve optimisation problems. Particle Swarm Optimisation (PSO) is a type of swarm computation …
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Markerless multiple-view human motion analysis using swarm optimisation and subspace learning
… multiple-view studio-based video sequences using particle swarm optimisation and charting, a subspace learning technique.In our first framework, we formulate, and perform, human motion tracking as a multi-dimensional non-linear optimisation problem, solved using particle swarm optimisation (PSO), …
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Optimum shear strengthening of reinforced concrete beams
… straps were investigated. Two popular optimisation algorithms namely the genetic algorithm (GA) and particle swarm optimisation (PSO) were coded and tested with six test functions. These algorithms were used to find the optimum shear retrofitting configurations and also to reduce the …
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Short term load forecasting based on hybrid artificial neural networks and particle swarm optimisation
… Fuzzy Logic (FL), Expert Systems (ES), and Particle Swarm Optimisation (PSO). Hybrid versions of these methods, where two or more CI methods are amalgamated in a process to forecast future load, have also been used. iv In this research, a traditional forecasting technique, Multiple Linear …
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Design and analysis of current stress minimalisation controllers in multi-active bridge DC-DC converters.
… (DAB). This is the simplest form of MAB, where particle swarm optimisation (PSO) is implemented offline to obtain optimal triple phase shift (TPS) parameters, for minimising the RMS current. This is achieved by applying PSO on DAB steady-state model, with generic per unit expressions of …
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Stand-alone solar-pv hydrogen energy systems incorporating reverse osmosis
… between applying (simplistic) predictive/optimisation techniques compared to intelligent tools in renewable energy systems. This is achieved through applying intelligent tools such as Neural Networks and Particle Swarm Optimisation for different aspects that govern system design and …
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Modelling and Tracking of the Global Maximum Power Point in Shaded Solar PV Systems Using Computational Intelligence
… Incremental conductance (IC), Fuzzy Logic (FL), Particle Swarm Optimisation (PSO) and the Firefly Optimisation (FA). The algorithms are tested under different weather conditions including partial shading. The Particle Swarm and Firefly algorithm performed relatively the same and were chosen to be …
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Flood risk assessment using multi-sensor remote sensing, geographic information system, 2D hydraulic and machine learning based models
… probability and hazard. The RF was optimised by particle swarm optimisation (PSO) algorithm. Both models were verified and calibrated by cross validation and sensitivity analysis to create a coupled PFF– FF probability mapping. The results showed high accuracy in generating a coupled PFF–FF …
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Strategic Environmental Assessment for Municipal Water Demand Based on Climate Change
… a Gravitational Search Algorithm (GSA-ANN) and Particle Swarm Optimisation (PSO-ANN). The SSA technique is adopted to decompose the time series of water consumption and climate variables to detect the stochastic signal for each time series. In the same context, the hybrid algorithms are used to …
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Efficient radio resource management in integrated terrestrial and non-terrestrial networks
… problem in the ITNTN as a multi-objective optimisation problem (MOOP) that jointly maximises the total data rate of the ITNTN while minimising the probability of mobility-induced handoffs. The problem is subjected to constraints on the resource budget and minimum user QoS requirements in …