Christian Veenhuis - Academia.edu (original) (raw)

Papers by Christian Veenhuis

This paper presents the WANDA Workbench, which is an open frameworkfor electronic data processing... more This paper presents the WANDA Workbench, which is an open frameworkfor electronic data processing. The framework provides generic interfaces for'plugin'applications for graphical user interfaces (client desktop with client plug-ins) andprocessing modules (server with server plug-ins). The applied plug-in concept allowsfor the functional extension of the workbench without changing the framework. Moreover, for data modeling, messaging and system configuration the eXtensible MarkupLanguage (XML) is implemented, which ...

ENFHEX news-Bulletin of the European Network of Forensic Handwriting Experts, 2004

The computer-based identification of a writer on the basis of a digitized piece of handwriting is... more The computer-based identification of a writer on the basis of a digitized piece of handwriting is a challenging task for pattern recognition. A number of systems have been in use in Europe, the United States, and Australia. However, most of these systems are becoming increasingly outdated. Latest research results in digital image processing and pattern recognition are not being considered in current practice. Moreover, common data standards, procedures, and generic system environments are lacking.

Proc. 3rd International Conference on Hybrid Intelligent Systems, 2003

Abstract. This paper presents the WANDA Workbench, which is an open framework for electronic data... more Abstract. This paper presents the WANDA Workbench, which is an open framework for electronic data processing. The framework provides generic interfaces for'plugin'applications for graphical user interfaces (client desktop with client plug-ins) and processing modules (server with server plug-ins). The applied plug-in concept allows for the functional extension of the workbench without changing the framework. Moreover, for data modeling, messaging and system configuration the eXtensible Markup Language (XML) is ...

Transactions on Computational Science XXI, Nov 2013

In recent years a number of web-technology supported communities of humans have been developed. S... more In recent years a number of web-technology supported communities of humans have been developed. Such a web community is able to let emerge a collective intelligence with a higher performance in solving problems than the single members of the community. Thus, collective intelligence systems are explicitly designed to take advantage of these increased capabilities. A well-known collective intelligence system is Wikipedia, the web encyclopedia. It uses a collaborative web community of authors, which improves and completes the content of articles. The quality of a certain number of these articles comes close to some degree to that of a famous printed encyclopedia. Based on such successes of collective intelligence systems, the question arises, whether such a collaborative web community could also be capable of function optimization. This paper introduces an optimization algorithm called Community Optimization (CO), which optimizes a function by simulating a collaborative web community, which edits or improves an article-base, or, more general, a knowledge-base. The knowledge-base represents the problem to be solved and is realized as a real valued vector. The different vector components (decision variables) represent different topics contained in this knowledge-base. Thus, the dimension of the problem is the number of topics to be improved by the simulated community, whereby the dimension remains static. In order to realize this, CO implements a behavioral model of collaborative human communities derived from the human behavior that can be observed within certain web communities (e.g., Wikipedia or open source communities). The introduced CO method is applied to eight well-known benchmark problems for lower as well as higher dimensions. CO turns out to be the best choice in 9 cases and the Fully Informed Particle Swarm Optimization (FIPS) as well as Differential Evolution (DE) approaches in 4 cases. Concerning the high dimensional problems, CO significantly outperformed FIPS as well as DE in 6 of 8 cases and seems to be a suitable approach for high dimensional problems.

Proc. 16th Portuguese Conference on Artificial Intelligence (EPIA 2013), Sep 9, 2013

Evolving constants in Genetic Programming is still an open issue. As real values they cannot be i... more Evolving constants in Genetic Programming is still an open issue. As real values they cannot be integrated in GP trees in a direct manner, because the nodes represent discrete symbols. Present solutions are the concept of ephemeral random constants or hybrid approaches, which have additional computational costs. Furthermore, one has to change the GP algorithm for them. This paper proposes a concept, which does not change the GP Algorithm or its components. Instead, it introduces structure-based constants realized as functions, which can be simply added to each function set while keeping the original GP approach. These constant functions derive their constant values from the tree structures of their child-trees (subtrees). That is, a constant is represented by a tree structure being this way under the influence of the typical genetic operators like subtree crossover or mutation. These structure-based constants were applied to symbolic regression problems. They outperformed the standard approach of ephemeral random constants. Their results together with their better properties make the structure-based constant concept a possible candidate for the replacement of the ephemeral random constants.

Proc. 4th International Conference on Intelligent Systems Design and Application, 2004

Proc. of the 10th international conference on Parallel Problem Solving from Nature: PPSN X, 2008

The representation used in Particle Swarm Optimization (PSO) is an n-dimensional vector. If you w... more The representation used in Particle Swarm Optimization (PSO) is an n-dimensional vector. If you want to apply the PSO method, you have to encode your problem as fix-sized vector. But many problem domains have solutions of unknown sizes as for instance in data clustering where you often don’t know the number of clusters in advance. In this paper a set-based PSO is proposed which replaces the position and velocity vectors by position and velocity sets realizing this way a PSO with variable length representation. All operations of the PSO update equations are redefined in an appropriate manner. Additionally, an operator reducing set bloating effects is introduced. The presented approach is applied to well-known data clustering problems and performs better as other algorithms on them.

Proc. of the 12th International Conference on Intelligent Systems Design and Applications, 2012

Transactions on Computational Science VIII, 2010

In recent years a swarm-based optimization methodology called Particle Swarm Optimization (PSO) h... more In recent years a swarm-based optimization methodology called Particle Swarm Optimization (PSO) has developed. If one wants to apply PSO one has to specify several parameters as well as to select a neighborhood topology. Several topologies being widely used can be found in literature. This raises the question, which one fits best to your application at hand. To get rid of this topology selection problem, a new concept called Polymorphic Particle Swarm Optimization (PolyPSO) is proposed. PolyPSO generalizes the standard update rule by a polymorphic update rule. The mathematical expression of this polymorphic update rule can be changed on symbolic level. This polymorphic update rule is an adaptive update rule changing symbols based on accumulative histograms and roulette-wheel sampling. PolyPSO is applied to four typical benchmark functions known from literature. In most cases it outperforms the other PSO variants under consideration. Since PolyPSO performs either as best or second best it can be used as alternative to solve this way the topology selection problem. Additionally, PolyPSO significantly outperforms the standard PSO methods in higher dimensional problems.

Proc. of the 2009 International Conference on Adaptive and Intelligent Systems, 2009

In recent years a swarm-based optimization methodology called Particle Swarm Optimization (PSO) h... more In recent years a swarm-based optimization methodology called Particle Swarm Optimization (PSO) has developed. If one wants to apply PSO one has to specify several parameters as well as to select a neighborhood topology. Several topologies being widely used can be found in literature. This raises the question, which one fits best to your application at hand. To get rid of this topology selection problem, a new concept called Polymorphic Particle Swarm Optimization (PolyPSO) is proposed. PolyPSO generalizes the standard update rule by a polymorphic update rule. The mathematical expression of this polymorphic update rule can be changed on symbolic level. This polymorphic update rule is an adaptive update rule changing symbols based on accumulative histograms and roulette-wheel sampling. PolyPSO is applied to four typical benchmark functions known from literature. In most cases it outperforms the other PSO variants under consideration. Since PolyPSO performs not worse it can be used as alternative to solve this way the topology selection problem.

Proc. 2nd International Conference on Hybrid Intelligent Systems, 2002

This paper proposes a document-oriented modeling concept for cellular automata (CA), which suppor... more This paper proposes a document-oriented modeling concept for cellular automata (CA), which supports the simple and rapid design of a huge variety of cellular automata. This modeling concept is realized as a domain-specific modeling language derived from XML (eXtensible Markup Language). XML is in general considered as the future for internet documents and data exchange. The main concept behind XML is to separate the content of a document from its layout (its appearance). The presented modeling concept uses a document for describing a whole cellular automaton. Like the content of a document is separated from its layout, the abstract cellular automaton is separated from a concrete implementation and programming language. Everyone can create and use XSL(T) stylesheets for translating cellular-automaton-documents into ready to use source-code (covering the adequate cellular-automaton-functionality) as well as for documentation and exchange of the realised CA.

Proc. of the 2009 IEEE international conference on Systems, Man and Cybernetics, 2009

In recent years a new evolutionary algorithm for optimization in continuous spaces called Differe... more In recent years a new evolutionary algorithm for optimization in continuous spaces called Differential Evolution (DE) has developed. If one wants to apply DE one has to specify several parameters as well as to select a scheme. Several schemes being widely used can be found in literature. This raises the question, which one fits best to your application at hand. To get rid of this scheme selection problem, a new concept called Polymorphic Differential Evolution (PolyDE) is proposed. PolyDE generalizes the standard schemes by a polymorphic scheme. The mathematical expression of this polymorphic scheme can be changed on symbolic level. This polymorphic scheme is an adaptive scheme changing symbols based on accumulative histograms and roulette-wheel sampling. PolyDE is applied to four typical benchmark functions known from literature and its performance is ranked between the top and middle region compared to all standard DE schemes. Since PolyDE performs not worse than the other schemes it can be used as alternative to them solving this way the scheme selection problem. The best performance is obtained for the multimodal functions.

International Journal of Hybrid Intelligent Systems, 2006

This paper introduces a new approach to multi-objective Particle Swarm Optimization (PSO). The ap... more This paper introduces a new approach to multi-objective Particle Swarm Optimization (PSO). The approach is based on the recently proposed Fuzzy-Pareto-Dominance (FPD) relation. FPD is a generic ranking scheme, where ranking values are mapped to element vectors of a set. These ranking values are directly computed from the element vectors of the set and can be used to perform rank operations (e.g. selecting the "largest") with the vectors within the given set. FPD can be seen as a paradigm or metaheuristic to formally expand single-objective optimization algorithms to multi-objective optimization algorithms, as long as such vector-sets can be defined. This was already shown for the Standard Genetic Algorithm. Here, we explore the application of this concept to PSO, where a swarm of particles is maintained. The resulting PSO f 2r algorithm is studied on a fundamental optimization problem (so-called Pareto-Box-Problem) where a complete analysis is possible. The PSO f 2r algorithm is shown to handle the case of a larger number of objectives, and shows similar properties like the (single-objective) PSO. Recently, the multivariate ranking scheme Fuzzy-Pareto-Dominance (FPD) was introduced . FPD maps a set of n vectors into the [0, 1] n range, to

Proc. of the 2007 IEEE Congress on Evolutionary Computation, 2007

One issue in applying Particle Swarm Optimization (PSO) is to find a good working set of paramete... more One issue in applying Particle Swarm Optimization (PSO) is to find a good working set of parameters. The standard settings often work sufficiently but don't exhaust the possibilities of PSO. Furthermore, a trade-off between accuracy and computation time is of interest for complex evaluation functions. This paper presents results for using an EMO approach to optimize PSO parameters as well as to find a set of trade-offs between mean fitness and swarm size. It is applied to four typical benchmark functions known from literature. The results indicate that using an EMO approach simplifies the decision process of choosing a parameter set for a given problem.

ENFHEX news - Bulletin of the European Network of Forensic Handwriting Experts, 2004

This paper presents the WANDA Workbench, which is an open framework for electronic data processin... more This paper presents the WANDA Workbench, which is an open framework for electronic data processing. The framework provides generic interfaces for 'plug-in' applications for graphical user interfaces (client desktop with client plug-ins) and processing modules (server with server plug-ins). The applied plug-in concept allows for the functional extension of the workbench without changing the framework. Moreover, for data modeling, messaging and system configuration the eXtensible Markup Language (XML) is implemented, which supports the interoperability with existing applications and allows for continuous adaptations to the evolving state of technology.

Proc. 6th International Conference on Hybrid Intelligent Systems, 2006

One issue in applying PSO is to find a good working set of parameters. The standard settings are ... more One issue in applying PSO is to find a good working set of parameters. The standard settings are often work sufficiently but donÂ¿t exhaust the possibilities of PSO. This paper proposes an extended Meta-PSO approach to optimize the PSO parameters as well as the neighborhood topology for a given problem by PSO itself. It is applied to four typical benchmark functions known from literature. The good results indicate that PSO is capable of optimizing itself.

Proc. of the 12th European Conference on Genetic Programming, 2009

In recent years a new evolutionary algorithm for optimization in continuos spaces called Differen... more In recent years a new evolutionary algorithm for optimization in continuos spaces called Differential Evolution (DE) has developed. DE turns out to need only few evaluation steps to minimize a function. This makes it an interesting candidate for problem domains with high computational costs as for instance in the automatic generation of programs. In this paper a DE-based tree discovering algorithm called Tree based Differential Evolution (TreeDE) is presented. TreeDE maps full trees to vectors and represents discrete symbols by points in a real-valued vector space providing this way all arithmetical operations needed for the different DE schemes. Because TreeDE inherits the ’speed property’ of DE, it needs only few evaluations to find suitable trees which produce comparable and better results as other methods.

Proc. 6th International Conference on Soft Computing, 2000

We propose a semantic model for evolutionary computation, which supports the rapid design of a hu... more We propose a semantic model for evolutionary computation, which supports the rapid design of a huge variety of evolutionary-algorithm-structures and can be represented in XML. Moreover, a designed evolutionary-computationmodel can also be used as compiler input to generate ready to use object-oriented code covering the adequate evolutionarycomputation-functionality as well as for documentation and exchanging the realised algorithm. The basic concept of the model is founded in a such called component hierarchy, where operators and basic algorithms are handled as programmable nodes of a structural tree and where the structural tree describes the computation flow. Within this paper the description of the semantic model is presented followed by a detailed example. It will be shown how the proposed approach enables a more abstract handling of the evolutionary algorithms, and how it speeds up the algorithm design. Also, it will be presented how rapid structural changes of the evolutionary algorithm might be performed by simple changing the operator hierarchy or by the replacement of the programmable nodes.

Swarm Intelligence and Data Mining, 2006

Data clustering is concerned with the division of a set of objects into groups of similar objects... more Data clustering is concerned with the division of a set of objects into groups of similar objects. In social insects there are many examples of clustering processes. Brood sorting observed in ant colonies can be considered as clustering according to the developmental state of the larvae. Also nest cleaning by forming piles of corpse or items is another example. These observed sorting and cluster capabilities of ant colonies have already been the inspiration of an ant-based clustering algorithm.

Proc. 3rd International Conference on Hybrid Intelligent Systems, 2003

This paper presents the WANDA Workbench, which is an open framework for electronic data processin... more This paper presents the WANDA Workbench, which is an open framework for electronic data processing. The framework provides generic interfaces for 'plugin' applications for graphical user interfaces (client desktop with client plug-ins) and processing modules (server with server plug-ins). The applied plug-in concept allows for the functional extension of the workbench without changing the framework. Moreover, for data modeling, messaging and system configuration the eXtensible Markup Language (XML) is implemented, which supports the interoperability with existing applications and allows for continuous adaptations to the evolving state of technology.

ENFHEX news-Bulletin of the European Network of Forensic Handwriting Experts, 2004

Proc. 3rd International Conference on Hybrid Intelligent Systems, 2003

Transactions on Computational Science XXI, Nov 2013

Proc. 16th Portuguese Conference on Artificial Intelligence (EPIA 2013), Sep 9, 2013

Proc. 4th International Conference on Intelligent Systems Design and Application, 2004

Proc. of the 10th international conference on Parallel Problem Solving from Nature: PPSN X, 2008

Proc. of the 12th International Conference on Intelligent Systems Design and Applications, 2012

Transactions on Computational Science VIII, 2010

Proc. of the 2009 International Conference on Adaptive and Intelligent Systems, 2009

In recent years a swarm-based optimization methodology called Particle Swarm Optimization (PSO) h... more In recent years a swarm-based optimization methodology called Particle Swarm Optimization (PSO) has developed. If one wants to apply PSO one has to specify several parameters as well as to select a neighborhood topology. Several topologies being widely used can be found in literature. This raises the question, which one fits best to your application at hand. To get rid of this topology selection problem, a new concept called Polymorphic Particle Swarm Optimization (PolyPSO) is proposed. PolyPSO generalizes the standard update rule by a polymorphic update rule. The mathematical expression of this polymorphic update rule can be changed on symbolic level. This polymorphic update rule is an adaptive update rule changing symbols based on accumulative histograms and roulette-wheel sampling. PolyPSO is applied to four typical benchmark functions known from literature. In most cases it outperforms the other PSO variants under consideration. Since PolyPSO performs not worse it can be used as alternative to solve this way the topology selection problem.

Proc. 2nd International Conference on Hybrid Intelligent Systems, 2002

Proc. of the 2009 IEEE international conference on Systems, Man and Cybernetics, 2009

International Journal of Hybrid Intelligent Systems, 2006

Proc. of the 2007 IEEE Congress on Evolutionary Computation, 2007

ENFHEX news - Bulletin of the European Network of Forensic Handwriting Experts, 2004

Proc. 6th International Conference on Hybrid Intelligent Systems, 2006

Proc. of the 12th European Conference on Genetic Programming, 2009

Proc. 6th International Conference on Soft Computing, 2000

Swarm Intelligence and Data Mining, 2006

Proc. 3rd International Conference on Hybrid Intelligent Systems, 2003

This paper presents the WANDA Workbench, which is an open framework for electronic data processin... more This paper presents the WANDA Workbench, which is an open framework for electronic data processing. The framework provides generic interfaces for 'plugin' applications for graphical user interfaces (client desktop with client plug-ins) and processing modules (server with server plug-ins). The applied plug-in concept allows for the functional extension of the workbench without changing the framework. Moreover, for data modeling, messaging and system configuration the eXtensible Markup Language (XML) is implemented, which supports the interoperability with existing applications and allows for continuous adaptations to the evolving state of technology.