A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

A Dynamic Migration Model for Self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

A Dynamic Migration Model for self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Design of a Self-Adaptive Down-Hole Layered Steam Injector and Its Application

Layered steam injection, widely used in Liaohe Oilfield at Present, is an effective recovery technique to heavy oil reserves. Which makes the steam front-peak push forward uniformly, the amount of steam injection be assigned rationally, and the effect of injection steam be obtained as expected. To maintain a fixed ratio of layered steam injection and solve the problem of nonadjustable hole diameter with the change of layer pressure in the existing injectors, a new method is proposed in this paper to design layered steam injectors based on the dynamic balance theory. According to gas-liquid two-phase flow theory and beat transfer theory, the energy equation and the heat conduction equation in boreholes are developed. By analyzing the energy equilibrium of water-steam passing through the injector hole, we find an expression to describe the relation between the cross-sectional area of injector hole and the layer pressure. With this expression, we provide a new set of calculation methods and write the corresponding computer program to design and calculate the main parameters of a steam injector. The actual measurement data show that the theoretically calculated results are accurate, the software runs reliably, and they provide the design of self-adjustable layered steam injectors with the theoretical foundation.

Design of a Self-Adaptive Down-Hole Layered Steam Injector and Its Application

Layered steam injection, widely used in Liaohe Oilfield at present, is an effective recovery technique to heavy oil reserves. Which makes the steam front-peak push forward uniformly, the amount of steam injection be assigned rationally, and the effect of injection steam be obtained as expected. To maintain a fixed ratio of layered steam injection and solve the problem of nonadjustable hole diameter with the change of layer pressure in the existing injectors, a new method is proposed in this paper to design layered steam injectors based on the dynamic balance theory According to gas-liquid two-phase flow theory and heat transfer theory, the energy equation and the heat conduction equation in boreholes are developed. By analyzing the energy equilibrium of water-steam passing through the injector hole, we find an expression to describe the relation between the cross-sectional area of injector hole and the layer pressure. With this expression, we provide a new set of calculation methods and write the corresponding computer program to design and calculate the main parameters of a steam injector. The actual measurement data show that the theoretically calculated results are accurate, the software runs reliably, and they provide the design of self-adjustable layered steam injectors with the theoretical foundation.

Self-adaptive optical systems for long-distance flying optics

The focusing characteristics of long-distance flying optics were studied systemically for TEMmn Gaussian beams. The results show that the ABCD law of parameter q can be extended to Gaussian modes of any order when waist radius w in the imaginary part of parameter q is replaced by Rayleigh range Z(R) of a certain resonator in the equation. The difference between the real focal length and the geometric focal length, defined as Delta f, was calculated for laser applications. A novel self-adaptive optical system was demonstrated for precisely controlling the focusing characteristics of long-distance flying optics, Theoretical analyses and experimental results were consistent. (c) 2006 Optical Society of America.

A self-adaptive genetic algorithm applied to multi-objective optimization of an airfoil

Genetic algorithms (GAs) have been used to tackle non-linear multi-objective optimization (MOO) problems successfully, but their success is governed by key parameters which have been shown to be sensitive to the nature of the particular problem, incorporating concerns such as the numbers of objectives and variables, and the size and topology of the search space, making it hard to determine the best settings in advance. This work describes a real-encoded multi-objective optimizing GA (MOGA) that uses self-adaptive mutation and crossover, and which is applied to optimization of an airfoil, for minimization of drag and maximization of lift coefficients. The MOGA is integrated with a Free-Form Deformation tool to manage the section geometry, and XFoil which evaluates each airfoil in terms of its aerodynamic efficiency. The performance is compared with those of the heuristic MOO algorithms, the Multi-Objective Tabu Search (MOTS) and NSGA-II, showing that this GA achieves better convergence.

Patterned self-adaptive polymer brushes by "grafting to" approach and microcontact printing

Patterned self-adaptive PS/P2VP mixed polymer brushes were prepared by "grafting to" approach combining with microcontact printing (muCP). The properties of the patterned surface were investigated by lateral force microscopy (LFM), XPS and water condensation figures. In the domains with grafted P2VP, the PS/P2VP mixed brushes demonstrated reversible switching behavior upon exposure to selective solvents for different components. The chemical composition of the top layer as well as the surface wettability can be well tuned due to the perpendicular phase segregation in the mixed brushes. While in the domains without grafted P2VP, the grafted PS did not have the capability of switching. The development and erasing of the pattern is reversible under different solvent treatment.

Natural inspiration for self-adaptive systems

The emergent behaviour of autonomic systems, together with the scale of their deployment, impedes prediction of the full range of configuration and failure scenarios; thus it is not possible to devise management and recovery strategies to cover all possible outcomes. One solution to this problem is to embed self-managing and self-healing abilities into such applications. Traditional design approaches favour determinism, even when unnecessary. This can lead to conflicts between the non-functional requirements. Natural systems such as ant colonies have evolved cooperative, finely tuned emergent behaviours which allow the colonies to function at very large scale and to be very robust, although non-deterministic. Simple pheromone-exchange communication systems are highly efficient and are a major contribution to their success. This paper proposes that we look to natural systems for inspiration when designing architecture and communications strategies, and presents an election algorithm which encapsulates non-deterministic behaviour to achieve high scalability, robustness and stability.

Generic support for policy-based self-adaptive systems

This paper presents a policy definition language which forms part of a generic policy toolkit for autonomic computing systems in which the policies themselves can be modified dynamically and automatically. Targeted enhancements to the current state of practice include: policy self-adaptation where the policy itself is dynamically modified to match environmental conditions; improved support for non autonomics-expert developers; and facilitating easy deployment of adaptive policies into legacy code. The policy definition language permits powerful expression of self-managing behaviours and facilitates a diverse policy behaviour space. Features include support for multiple versions of a given policy type, multiple configuration templates, and meta policies to dynamically select between policy instances. An example deployment scenario illustrates advanced functionality in the context of a multi policy stock trading system which is sensitive to environmental volatility.

Self-adaptive combination of global tabu search and local search for nonlinear equations

Solving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a self-adaptive combination of a metaheuristic with a classical local search method is able to converge to some difficult problems that are not solved by Newton-type methods.

The Human in the Loop: User Participation in Self-Adaptive Software

Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.