The field of evolutionary computation has experienced tremendous growth over the past 20 years, resulting in a wide variety of evolutionary algorithms and applications. The result poses an interesting dilemma for many...
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ISBN:
(纸本)9781450300735
The field of evolutionary computation has experienced tremendous growth over the past 20 years, resulting in a wide variety of evolutionary algorithms and applications. The result poses an interesting dilemma for many practitioners in the sense that, with such a wide variety of algorithms and approaches, it is often hard to se the relationships between them, assess strengths and weaknesses, and make good choices for new application *** tutorial is intended to give an overview of a general EC framework that can help compare and contrast approaches, encourages crossbreeding, and facilitates intelligent design choices. The use of this framework is then illustrated by showing how traditional EAs can be compared and contrasted with it, and how new EAs can be effectively designed using ***, the framework is used to identify some important open issues that need further research
This paper presents several evolutionary computation techniques and discusses their applicability to nonlinear programming problems. On the basis of this presentation we discuss also a construction of a new hybrid opt...
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Biological systems are inherently stochastic, a fact which is often ignored when simulating genetic circuits. Synthetic biology aims to design genetic circuits de novo, and cannot therefore afford to ignore the effect...
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ISBN:
(纸本)9781424441242
Biological systems are inherently stochastic, a fact which is often ignored when simulating genetic circuits. Synthetic biology aims to design genetic circuits de novo, and cannot therefore afford to ignore the effects of stochastic behavior. Since computational design tools will be essential for large-scale synthetic biology, it is important to develop an understanding of the role of stochasticity in molecular biology, and incorporate this understanding into computational tools for genetic circuit design. We report upon an investigation into the combination of evolutionary algorithms and stochastic simulation for genetic circuit design, to design regulatory systems based on the Bacillus subtilis sin operon.
The QRS complex is a very informative component of the electrocardiogram (ECG). It corresponds to ventricular depolarization of the human heart. The detection of QRS complexes provides the fundamental basis for any au...
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ISBN:
(纸本)9783319023090
The QRS complex is a very informative component of the electrocardiogram (ECG). It corresponds to ventricular depolarization of the human heart. The detection of QRS complexes provides the fundamental basis for any automated ECG analysis system. In this paper, evolutionary computation is applied for preprocessing filter design in QRS detection algorithm. In the proposed solution, ECG signal bandwidth is separated into multiple sub-bands and corresponding filters are optimized to minimize the number of false QRS detections. The algorithm performance has been evaluated with the MIT/BIH arrhythmia database. The obtained results show significant improvement, in terms of false detection reduction for ECG signals with high level of noise, when compared to the other available QRS detection algorithms.
Optimal integration of electric vehicles (EVs) into modern power grids plays a promising role in future operation of smart power systems. The role of aggregators as e-mobility service providers is getting investigated...
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ISBN:
(纸本)9781467360029
Optimal integration of electric vehicles (EVs) into modern power grids plays a promising role in future operation of smart power systems. The role of aggregators as e-mobility service providers is getting investigated steadily in recent times and forms a fruitful ground for control of EN' charging. Within this paper, a policy-based control approach is shown that applies an evolutionary simulation optimization procedure for learning valid charging policies offline, that lead to accurate charging decisions online during operation. This approach provides a trade-off between local and distributed control, since the centrally applied learning procedure ensures satisfaction of the operator's requirements during the learning phase, where final control is applied decentrally after distributing the learned policies to the agents. Since the needed information that the aggregator has to provide to the agents is crucial, further analysis on the achieved control policies concerning their data requirements are conducted.
Data fusion approaches are nowadays needed and also a challenge in many areas, like sensor systems monitoring complex processes. This paper explores evolutionary computation approaches to sensor fusion based on unsupe...
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ISBN:
(纸本)9781424481262
Data fusion approaches are nowadays needed and also a challenge in many areas, like sensor systems monitoring complex processes. This paper explores evolutionary computation approaches to sensor fusion based on unsupervised nonlinear transformations between the original sensor space (possibly highly-dimensional) and lower dimensional spaces. Domain-independent implicit and explicit transformations for Visual Data Mining using Differential Evolution and Genetic Programming aiming at preserving the similarity structure of the observed multivariate data are applied and compared with classical deterministic methods. These approaches are illustrated with a real world complex problem: Failure conditions in Auxiliary Power Units in aircrafts. The results indicate that the evolutionary approaches used were useful and effective at reducing dimensionality while preserving the similarity structure of the original data. Moreover the explicit models obtained with Genetic Programming simultaneously covered both feature selection and generation. The evolutionary techniques used compared very well with their classical counterparts, having additional advantages. The transformed spaces also help in visualizing and understanding the properties of the sensor data.
In recent years, the field of computational Intelligence and Games (CIG) has enjoyed rapid progress and a sharp rise in popularity. In this field, algorithms from across the computational intelligence spectrum are tes...
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ISBN:
(纸本)9781450343237
In recent years, the field of computational Intelligence and Games (CIG) has enjoyed rapid progress and a sharp rise in popularity. In this field, algorithms from across the computational intelligence spectrum are tested on benchmarks based on e.g. board games and video games, and new CI-based solutions are developed for problems in game development and game design. This tutorial will give an overview of key research challenges and methods of choice in CIG. The tutorial is divided in two parts, where the second part builds on methods and results introduced in the first part. Level: introductory. No particular background is assumed beyond basic knowledge of computational intelligence methods and an interest in games.
Cyber-physical systems (CPSs) are designed to integrate computation and physical processes through constantly interacting with the physical environment. The complexity and uncertainty of the environment often come up ...
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ISBN:
(纸本)9798350322637
Cyber-physical systems (CPSs) are designed to integrate computation and physical processes through constantly interacting with the physical environment. The complexity and uncertainty of the environment often come up with unpredictable situations, which place high demands on the dynamic adaptability of CPSs. Further, as the environment evolves, the CPS needs to constantly evolve itself to adapt to the changing environment. This paper presents a research plan that aims to develop a novel framework to address CPS design challenges under uncertain environments. We propose to utilize evolutionary computation and reinforcement learning techniques to design control policies that can adapt to the dynamic changes and uncertainties of the environment. Further, novel testing and evaluation approaches that can generate test cases while adapting to dynamic changes in the system and the environment will be explored.
The collapse of the Californian electricity market system in 2001 has highlighted urgency in research in intelligent electricity trading systems and strategies involving both suppliers and customs. In their trading sy...
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ISBN:
(纸本)9781424413393
The collapse of the Californian electricity market system in 2001 has highlighted urgency in research in intelligent electricity trading systems and strategies involving both suppliers and customs. In their trading systems, power generation companies under the New Electricity Trading Arrangement (NETA) of the UK are now developing gaming strategies. However, modelling of such "intelligent" market behaviours is extremely challenging, because traditional mathematical and computer modelling techniques cannot cope with the involvement of game theory. In this paper, evolutionary computation enabled modelling of such system is presented. Both competitive and cooperative game theory strategies are taken into account in evolving the intelligent model. The model then leads to intelligent trading strategy development and decision support. Experimental tests, verification and validation are carried out with various strategies, using different model scales and data published by NETA. Results show that evolutionary computation enabled game theory involved modelling and decision making provides an effective tool for NETA trading analysis, prediction and support.
Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use ...
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ISBN:
(数字)9781119574293
ISBN:
(纸本)9781119573845
Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches. evolutionary computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book: Provides a representative sampling of real-world problems currently being tackled by practitioners Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence Consists of four main parts: Introduction to Scheduling Problems, computational Issues in Scheduling Problems, evolutionary computation, and evolutionary computations for Scheduling Problems Evoluti
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