Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications

A comprehensive study on modern optimization techniques for engineering applications

Rapid industrialization has fueled the need for effective optimization solutions, which has led to the widespread use of meta-heuristic algorithms. Among the repertoire of over 600, over 300 new methodologies have been developed in the last ten years. This increase highlights the need for a sophisticated grasp of these novel methods. The use of biological and natural phenomena to inform meta-heuristic optimization strategies has seen a paradigm shift in recent years. The observed trend indicates an increasing acknowledgement of the effectiveness of bio-inspired methodologies in tackling intricate engineering problems, providing solutions that exhibit rapid convergence rates and unmatched fitness scores. This study thoroughly examines the latest advancements in bio-inspired optimisation techniques. This work investigates each method’s unique characteristics, optimization properties, and operational paradigms to determine how revolutionary these approaches could be for problem-solving paradigms. Additionally, extensive comparative analyses against conventional benchmarks, such as metrics such as search history, trajectory plots, and fitness functions, are conducted to elucidate the superiority of these new approaches. Our findings demonstrate the revolutionary potential of bio-inspired optimizers and provide new directions for future research to refine and expand upon these intriguing methodologies. Our survey could be a lighthouse, guiding scientists towards innovative solutions rooted in various natural mechanisms

Technology Trends and Opportunities for Construction Industry and Lifecycle Management

Master's thesis in for Offshore Technology: Industrial Asset ManagementThe purpose of the report is to highlight methods that can make it easier for the construction industry and industry in general to benefit from new technology. The report is intended as a reference to technological solutions that along with some techniques, can streamline workflow for multiple tasks in planning, design, and operation and maintenance management. The problems focused on is how to: • Simplify the procurement and tracing of documentation • Optimize building stages, design, and Life Cycle Management (LCM) • Provide interactions between disciplines and employees using different software Scientific Platform are based on literature within technology trends. Some history and trends in digital technology are presented. Definition of roles and general terms related to documentation is derived from Norsk Standard and is interpreted on this basis. The report charts the use of individual software and technical setup of digital tools within CAD-engineering (Computer Aided Design), HDS-technology (High Definition Surveying), and gaming technology. This technology combined with cloud-services to support planning, design and management of building stages. Later to support LCM of facilities and businesses' ERP-systems (Enterprise Resource Planning). Use of Robotic Process Automation (RPA) and Artificial Intelligence (AI), for document control tasks. The result of the report is that several suppliers provide services and products accessible through web. Setup and implementation will require some work and knowledge for business and organizations, but the gain largely seems to justify the use of resources for this purpose. Particularly through IOT-interactions (Internet of Things), cloud-services and free downloadable applications that may be considered as a paradigm shift related to the issues in the report. Also, presenting new platforms for engineering phases to support Building Information Modeling processes (BIM). With the use of Algorithmic Editors for encoding between computer programs without the need of data programmer expertise. To streamline workflows, reduce recreation of data, interactions between different software of various user level, and support of AI to optimize designing by adds-on for CAD-engineering (Computer Aided Design). Mobile devices like phones and tablets to support several of solutions and products presented is very accessible. It seems naturally to assume that the vast majority of people are familiar with technology related to smartphone applications for daily use. The use of resources for implementing the presented solutions have not been considered in this report. Some of the equipment presented can be interpreted as relatively expensive. Investment analysis would be sensible. The trend however, shows continues price drops and increased availability. At the same time as the user interface is being improved for both software and digital equipment. The conclusion, is that the construction industry, as well as Facility Management (FM). Within both, public, and private sector, can have much to gain using the technology and techniques presented in the report

Motion Planning

Motion planning is a fundamental function in robotics and numerous intelligent machines. The global concept of planning involves multiple capabilities, such as path generation, dynamic planning, optimization, tracking, and control. This book has organized different planning topics into three general perspectives that are classified by the type of robotic applications. The chapters are a selection of recent developments in a) planning and tracking methods for unmanned aerial vehicles, b) heuristically based methods for navigation planning and routes optimization, and c) control techniques developed for path planning of autonomous wheeled platforms

Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification

Sky image classification is crucial in meteorology to forecast weather and climatic conditions. The fine-grained cloud detection and recognition (FGCDR) algorithm is use to extract colour, inside texture and neighbour texture features from multiview of superpixels sky images. However, the FGCDR produced a substantial amount of redundant and insignificant features. The ant colony optimisation (ACO) algorithm have been used to select feature subset. However, the ACO suffers from premature convergence which leads to poor feature subset. Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. This algorithm consists of (i) Gaussian smoothness standard deviation method that formulates informative features within sky images; (ii) nearest-threshold based technique that converts feature map into a weighted directed graph to represent relationship between features; and (iii) an ant colony system with self-adaptive parameter technique for local pheromone update. The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. The Friedman test result is presented for the performance rank of six benchmark feature selection algorithms and FESSIC algorithm. The Man-Whitney U test is then performed to statistically evaluate the significance difference of the second rank and FESSIC algorithms. The experimental results for the proposed algorithm are superior to the benchmark image classification algorithms in terms of similarity value on Kiel, SWIMCAT and MGCD datasets. FESSIC outperforms other algorithms for average classification accuracy for the KSVM, MLP, RF and DT classifiers. The Friedman test has shown that the FESSIC has the first rank for all classifiers. Furthermore, the result of Man-Whitney U test indicates that FESSIC is significantly better than the second rank benchmark algorithm for all classifiers. In conclusion, the FESSIC can be utilised for image classification in various applications such as disaster management, medical diagnosis, industrial inspection, sports management, and content-based image retrieval

Computational Optimizations for Machine Learning

The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity

An investigation into the utilization of swarm intellingence for the control of the doubly fed induction generator under the influence of symmetrical and assymmetrical voltage dips.

Doctoral Degree. University of KwaZulu-Natal, Durban.The rapid depletion of fossil, fuels, increase in population, and birth of various industries has put a severe strain on conventional electrical power generation systems. It is because of this, that Wind Energy Conversion Systems has recently come under intense investigation. Among all topologies, the Doubly Fed Induction Generator is the preferred choice, owing to its direct grid connection, and variable speed nature. However, this connection has disadvantages. Wind turbines are generally placed in areas where the national grid is weak. In the case of asymmetrical voltage dips, which is a common occurrence near wind farms, the operation of the DFIG is negatively affected. Further, in the case of symmetrical voltage dips, as in the case of a three-phase short circuit, this direct grid connection poses a severe threat to the health and subsequent operation of the machine. Owing to these risks, there has been various approaches which are utilized to mitigate the effect of such occurrences. Considering asymmetrical voltage dips, symmetrical component theory allows for decomposition and subsequent elimination of negative sequence components. The proportional resonant controller, which introduces an infinite gain at synchronous frequency, is another viable option. When approached with the case of symmetrical voltage dips, the crowbar is an established method to expedite the rate of decay of the rotor current and dc link voltage. However, this requires the DFIG to be disconnected from the grid, which is against the rules of recently grid codes. To overcome such, the Linear Quadratic Regulator may be utilized. As evident, there has been various approaches to these issues. However, they all require obtaining of optimized gain values. Whilst these controllers work well, poor optimization of gain quantities may result in sub-optimal performance of the controllers. This work provides an investigation into the utilization of metaheuristic optimization techniques for these purposes. This research focuses on swarm-intelligence, which have proven to provide good results. Various swarm techniques from across the timeline spectrum, beginning from the well-known Particle Swarm Optimization, to the recently proposed African Vultures Optimization Algorithm, have been applied and analysed

HyperCell: A Bio-inspired Design Framework for Real-time Interactive Architectures

This pioneering research focuses on Biomimetic Interactive Architecture using “Computation”, “Embodiment”, and “Biology” to generate an intimate embodied convergence to propose a novel rule-based design framework for creating organic architectures composed of swarm-based intelligent components. Furthermore, the research boldly claims that Interactive Architecture should emerge as the next truly Organic Architecture. As the world and society are dynamically changing, especially in this digital era, the research dares to challenge the Utilitas, Firmitas, and Venustas of the traditional architectural Weltanschauung, and rejects them by adopting the novel notion that architecture should be dynamic, fluid, and interactive. This project reflects a trajectory from the 1960’s with the advent of the avant-garde architectural design group, Archigram, and its numerous intriguing and pioneering visionary projects. Archigram’s non-standard, mobile, and interactive projects profoundly influenced a new generation of architects to explore the connection between technology and their architectural projects. This research continues this trend of exploring novel design thinking and the framework of Interactive Architecture by discovering the interrelationship amongst three major topics: “Computation”, “Embodiment”, and “Biology”. The project aims to elucidate pioneering research combining these three topics in one discourse: “Bio-inspired digital architectural design”. These three major topics will be introduced in this Summary.   “Computation”, is any type of calculation that includes both arithmetical and nonarithmetical steps and follows a well-defined model understood and described as, for example, an algorithm. But, in this research, refers to the use of data storage, parametric design application, and physical computing for developing informed architectural designs. “Form” has always been the most critical focus in architectural design, and this focus has also been a major driver behind the application computational design in Architecture. Nonetheless, this research will interpret the term “Form” in architecture as a continual “information processor” rather than the result of information processing. In other words, “Form” should not be perceived only as an expressive appearance based computational outcome but rather as a real-time process of information processing, akin to organic “Formation”. Architecture embodying kinetic ability for adjusting or changing its shape with the ability to process the surroundings and feedback in accordance with its free will with an inherent interactive intelligent movement of a living body. Additionally, it is also crucial to address the question of whether computational technologies are being properly harnessed, if they are only used for form-generating purposes in architecture design, or should this be replaced with real-time information communication and control systems to produce interactive architectures, with embodied computation abilities?   “Embodiment” in the context of this research is embedded in Umberto Eco’s vision on Semiotics, theories underlying media studies in Marshall McLuhan’s “Body Extension” (McLuhan, 1964), the contemporary philosophical thought of “Body Without Organs” (Gilles Deleuze and Félix Guattari, 1983), the computational Logic of ‘Swarm Behavior’ and the philosophical notion of “Monadology” proposed by Gottfried Leibniz (Leibniz, 1714). Embodied computation and design are predominant today within the wearable computing and smart living domains, which combine Virtual and Real worlds. Technical progress and prowess in VR development also contribute to advancing 3D smart architectural design and display solutions. The proposed ‘Organic body-like architectural spaces’ emphasize upon the realization of a body-like interactive space. Developing Interactive Architecture will imply eliciting the collective intelligence prevalent in nature and the virtual world of Big Data. Interactive Architecture shall thus embody integrated Information exchange protocols and decision-making systems in order to possess organic body-like qualities.   “Biology”, in this research explores biomimetic principles intended to create purposedriven kinetic and organic architecture. This involves a detailed study/critique of organic architecture, generating organic shapes, performance optimization based digital fabrication techniques and kinetic systems. A holistic bio-inspired architecture embodies multiple performance criteria akin to natural systems, which integrate structural, infrastructure performances throughout the growth of an organic body. Such a natural morphogenesis process of architectural design explores what Janine M. Benyus described as “learning the natural process”. Profoundly influenced by the processes behind morphogenesis, the research further explores Evolutionary Development Biology (Evo-Devo) explaining how embryological regulation strongly affect the resulting formations. Evo-Devo in interactive architecture implies the development of architecture based on three fundamental principles: “Simple to Complex”, “Geometric Information Distribution”, and “On/Off Switch and Trigger.” The research seeks to create a relatively intelligent architectural body, and the tactile interactive spatial environment by applying the extracted knowledge from the study of the aforementioned principles of Evo-Devo in the following fashion: A. Extract a Self-Similar Componential System based approach from the “Simple to Complex” principle of Evo-Devo B. Extract the idea of “Collective Intelligence” from “Geometric information Distribution” principle of Evo-Devo C. Extract the principle of “Assembly Regulation” from “On/Off switch and trigger” principle of Evo-Devo The “HyperCell” research, through an elaborate investigation on the three aforementioned topics, develops a design framework for developing real-time adaptive spatial systems. HyperCell does this, by developing a system of transformable cubic elements which can self-organize, adapt and interact in real-time. These Hypercells shall comprise an organic space which can adjust itself in relation to our human bodies. The furniture system is literally reified and embodied to develop an intra-active space that proactively provokes human movement. The space thus acquires an emotive dimension and can become your pet, partner, or even friend, and might also involve multiple usabilities of the same space. The research and its progression were also had actively connected with a 5-year collaborative European Culture project: “MetaBody”. The research thus involves exploration of Interactive Architecture from the following perspectives: architectural design, digital architectural history trajectory, computational technology, philosophical discourse related to the embodiment, media and digital culture, current VR and body-related technology, and Evolutionary Developmental Biology. “HyperCell” will encourage young architects to pursue interdisciplinary design initiatives via the fusion of computational design, embodiment, and biology for developing bio-inspired organic architectures