1,720,971 research outputs found
Solving dynamic multi-objective optimisation problems using vector evaluated particle swarm optimisation
Get PDFThesis (PhD)--University of Pretoria, 2012.Most optimisation problems in everyday life are not static in nature, have multiple objectives and at least two of the objectives are in conflict with one another. However, most research focusses on either static multi-objective optimisation (MOO) or dynamic singleobjective optimisation (DSOO). Furthermore, most research on dynamic multi-objective optimisation (DMOO) focusses on evolutionary algorithms (EAs) and only a few particle swarm optimisation (PSO) algorithms exist. This thesis proposes a multi-swarm PSO algorithm, dynamic Vector Evaluated Particle Swarm Optimisation (DVEPSO), to solve dynamic multi-objective optimisation problems (DMOOPs). In order to determine whether an algorithm solves DMOO efficiently, functions are required that resembles real world DMOOPs, called benchmark functions, as well as functions that quantify the performance of the algorithm, called performance measures. However, one major problem in the field of DMOO is a lack of standard benchmark functions and performance measures. To address this problem, an overview is provided from the current literature and shortcomings of current DMOO benchmark functions and performance measures are discussed. In addition, new DMOOPs are introduced to address the identified shortcomings of current benchmark functions. Guides guide the optimisation process of DVEPSO. Therefore, various guide update approaches are investigated. Furthermore, a sensitivity analysis of DVEPSO is conducted to determine the influence of various parameters on the performance of DVEPSO. The investigated parameters include approaches to manage boundary constraint violations, approaches to share knowledge between the sub-swarms and responses to changes in the environment that are applied to either the particles of the sub-swarms or the non-dominated solutions stored in the archive. From these experiments the best DVEPSO configuration is determined and compared against four state-of-the-art DMOO algorithms.Computer Scienceunrestricte
Cone normal stepping
Get PDFDissertation (MSc)--University of Pretoria, 2018.This dissertation examines several methods of relief mapping, such as parallax mapping and cone step mapping, as well as methods for soft shadowing and ambient occlusion of relief maps. Ambient occlusion is an approximation of global illumination that only takes occlusion into account. New relief mapping methods are introduced to bridge the gap between distance elds and cone maps. The new methods allow calculating approximate distance elds from their cone map approximate ambient occlusion and soft shadows. The new methods are compared with linear, binary, and interval search as well as variants of cone mapping, such as relaxed cone mapping and quad cone mapping. These methods were evaluated with regards to performance and accuracy and were found to be similar in performance and accuracy than the existing methods. The new methods did not outperform existing methods on the tested scenes, but the new methods make use of approximate distance elds and remove the maximum cone angle limitation. It was also shown that in most cases linear search with interval mapping performed the best, given the error metric used.TM2019Computer ScienceMScUnrestricte
Cone normal stepping
Get PDFDissertation (MSc)--University of Pretoria, 2018.This dissertation examines several methods of relief mapping, such as parallax mapping and cone step mapping, as well as methods for soft shadowing and ambient occlusion of relief maps. Ambient occlusion is an approximation of global illumination that only takes occlusion into account. New relief mapping methods are introduced to bridge the gap between distance elds and cone maps. The new methods allow calculating approximate distance elds from their cone map approximate ambient occlusion and soft shadows. The new methods are compared with linear, binary, and interval search as well as variants of cone mapping, such as relaxed cone mapping and quad cone mapping. These methods were evaluated with regards to performance and accuracy and were found to be similar in performance and accuracy than the existing methods. The new methods did not outperform existing methods on the tested scenes, but the new methods make use of approximate distance elds and remove the maximum cone angle limitation. It was also shown that in most cases linear search with interval mapping performed the best, given the error metric used.Computer ScienceMScUnrestricte
Challenges Applying Dynamic Multi-objective Optimisation Algorithms to Real-World Problems
No full textMany optimisation problems have multiple conflicting goals, where at least one objective and/or constraint is dynamic in nature. These problems are referred to as dynamic multi-objective optimisation problems (DMOOPs). Most of the research in the field of dynamic multi-objective optimisation (DMOO) focuses on the development of new algorithms. However, there still remain a number of challenges to be addressed before the algorithms can be efficiently applied to real-world DMOO problems (RWPs). This chapter firstly presents a taxonomy of dynamic multi-objective optimisation (DMOO) RWPs and highlights the characteristics of these problems. These characteristics bring to light the challenges that should still be addressed when applying DMOO algorithms to RWPs.No Full Tex
Fitness Landscape Analysis of Feed-Forward Neural Networks
Get PDFThesis (PhD)--University of Pretoria, 2019.Neural network training is a highly non-convex optimisation problem with poorly understood properties. Due to the inherent high dimensionality, neural network search spaces cannot be intuitively visualised, thus other means to establish search space properties have to be employed. Fitness landscape analysis encompasses a selection of techniques designed to estimate the properties of a search landscape associated with an optimisation problem. Applied to neural network training, fitness landscape analysis can be used to establish a link between the properties of the error landscape and various neural network hyperparameters. This study applies fitness landscape analysis to investigate the influence of the search space boundaries, regularisation parameters, loss functions, activation functions, and feed-forward neural network architectures on the properties of the resulting error landscape. A novel gradient-based sampling technique is proposed, together with a novel method to quantify and visualise stationary points and the associated basins of attraction in neural network error landscapes.NRFComputer SciencePhDUnrestricte
Dynamic multi-objective optimization for financial markets
Get PDFDissertation (MEng)--University of Pretoria, 2019.The foreign exchange (Forex) market has over 5 trillion USD turnover per day. In addition,
it is one of the most volatile and dynamic markets in the world. Market conditions
continue to change every second. Algorithmic trading in Financial markets have received
a lot of attention in recent years. However, only few literature have explored the applicability
and performance of various dynamic multi-objective algorithms (DMOAs) in the
Forex market. This dissertation proposes a dynamic multi-swarm multi-objective particle
swarm optimization (DMS-MOPSO) to solve dynamic MOPs (DMOPs). In order to
explore the performance and applicability of DMS-MOPSO, the algorithm is adapted for
the Forex market. This dissertation also explores the performance of di erent variants
of dynamic particle swarm optimization (PSO), namely the charge PSO (cPSO) and
quantum PSO (qPSO), for the Forex market. However, since the Forex market is not
only dynamic but have di erent con
icting objectives, a single-objective optimization
algorithm (SOA) might not yield pro t over time. For this reason, the Forex market was
de ned as a multi-objective optimization problem (MOP). Moreover, maximizing pro t
in a nancial time series, like Forex, with computational intelligence (CI) techniques is
very challenging. It is even more challenging to make a decision from the solutions of a
MOP, like automated Forex trading. This dissertation also explores the e ects of ve decision
models (DMs) on DMS-MOPSO and other three state-of-the-art DMOAs, namely
the dynamic vector-evaluated particle swarm optimization (DVEPSO) algorithm, the
multi-objective particle swarm optimization algorithm with crowded distance (MOPSOCD)
and dynamic non-dominated sorting genetic algorithm II (DNSGA-II). The e ects
of constraints handling and the, knowledge sharing approach amongst sub-swarms were
explored for DMS-MOPSO. DMS-MOPSO is compared against other state-of-the-art
multi-objective algorithms (MOAs) and dynamic SOAs. A sliding window mechanism
is employed over di erent types of currency pairs. The focus of this dissertation is to
optimized technical indicators to maximized the pro t and minimize the transaction
cost.
The obtained results showed that both dynamic single-objective optimization (SOO)
algorithms and dynamic multi-objective optimization (MOO) algorithms performed better
than static algorithms on dynamic poroblems. Moreover, the results also showed that
a multi-swarm approach for MOO can solve dynamic MOPs.Computer ScienceMScUnrestricte
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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