Percorrer por autor "Yevseyeva, Iryna"
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- 3D fast convex-hull-based evolutionary multiobjective optimization algorithmPublication . Zhao, Jiaqi; Jiao, Licheng; Liu, Fang; Basto-Fernandes, Vitor; Yevseyeva, Iryna; Xia, Shixiong; Emmerich, Michael T.M.The receiver operating characteristic (ROC) and detection error tradeoff (DET) curves have been widely used in the machine learning community to analyze the performance of classifiers. The area (or volume) under the convex hull has been used as a scalar indicator for the performance of a set of classifiers in ROC and DET space. Recently, 3D convex-hull-based evolutionary multiobjective optimization algorithm (3DCH-EMOA) has been proposed to maximize the volume of convex hull for binary classification combined with parsimony and three-way classification problems. However, 3DCH-EMOA revealed high consumption of computational resources due to redundant convex hull calculations and a frequent execution of nondominated sorting. In this paper, we introduce incremental convex hull calculation and a fast replacement for non-dominated sorting. While achieving the same high quality results, the computational effort of 3DCH-EMOA can be reduced by orders of magnitude. The average time complexity of 3DCH-EMOA in each generation is reduced from to per iteration, where n is the population size. Six test function problems are used to test the performance of the newly proposed method, and the algorithms are compared to several state-of-the-art algorithms, including NSGA-III, RVEA, etc., which were not compared to 3DCH-EMOA before. Experimental results show that the new version of the algorithm (3DFCH-EMOA) can speed up 3DCH-EMOA for about 30 times for a typical population size of 300 without reducing the performance of the method. Besides, the proposed algorithm is applied for neural networks pruning, and several UCI datasets are used to test the performance.
- An automatic generation of textual pattern rules for digital content filters proposal, using grammatical evolution genetic programmingPublication . Basto-Fernandes, Vitor; Yevseyeva, Iryna; Frantz, Rafael Z.; Grilo, Carlos Fernando Almeida; Díaz, Noemí Pérez; Emmerich, Michael
- Building and Using an Ontology of Preference-Based Multiobjective Evolutionary AlgorithmsPublication . Li, Longmei; Yevseyeva, Iryna; Basto-Fernandes, Vitor; Trautmann, Heike; Jing, Ning; Emmerich, MichaelIntegrating user preferences in Evolutionary Multiobjective Optimization (EMO) is currently a prevalent research topic. There is a large variety of preference handling methods (originated from Multicriteria decision making, MCDM) and EMO methods, which have been combined in various ways. This paper proposes a Web Ontology Language (OWL) ontology to model and systematize the knowledge of preferencebased multiobjective evolutionary algorithms (PMOEAs). Detailed procedure is given on how to build and use the ontology with the help of Prot´eg´e. Different use-cases, including training new learners, querying and reasoning are exemplified and show remarkable benefit for both EMO and MCDM communities.
- Characterising Enterprise Application Integration Solutions as Discrete-Event SystemsPublication . Sawicki, Sandro; Frantz, Rafael Z.; Basto-Fernandes, Vitor; Fabricia Roos-Frantz, Fabricia; Yevseyeva, Iryna; Corchuelo, RafaelIt is not difficult to find an enterprise which has a software ecosystem composed of applications that were built using different technologies, data models, operating systems, and most often were not designed to exchange data and share functionalities. Enterprise Application Integration provides methodologies and tools to design and implement integration solutions. The state-of-the-art integration technologies provide a domain-specific language that enables the design of conceptual models for integration solutions. The analysis of integration solutions to predict their behaviour and find possible performance bottlenecks is an important activity that contributes to increase the quality of the delivered solutions, however, software engineers follow a costly, risky, and time-consuming approach. Integration solutions shall be understood as a discrete-event system. This chapter introduces a new approach based on simulation to take advantage of well-established techniques and tools for discrete-event simulation, cutting down cost, risk, and time to deliver better integration solutions.
- A Comparison of Cybersecurity Risk Analysis ToolsPublication . Roldán-Molina, Gabriela; Almache-Cueva, Mario; Silva-Rabadão, Carlos; Yevseyeva, Iryna; Basto-Fernandes, VitorThis paper presents ongoing work of a decision aiding software intended to support cyber risk and cyber threats analysis of an information and communication technology infrastructure. The work is focused on the evaluation of the most popular and relevant tools available for risk assessment and decision making in the cybersecurity domain. Their properties, metrics and strategies are analysed and their support for cybersecurity risk analysis, decision-making and prevention is assessed for the protection of an organization’s information assets.
- Corrigendum to “A spam filtering multi-objective optimization study covering parsimony maximization and three-way classification” [Applied Soft Computing Volume 48 (2016) 111–123]Publication . Basto-Fernandes, Vitor; Yevseyeva, Iryna; Méndez, José R.; Zhao, Jiaqi; Fdez-Riverola, Florentino; Emmerich, Michael T. M.
- Corrigendum to ‘Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms’ [Information Sciences volumes 367–368 (2016) 80–104]Publication . Zhao, Jiaqi; Basto-Fernandes, Vitor; Jiao, Licheng; Yevseyeva, Iryna; Maulana, Asep; Li, Rui; Bäck, Thomas; Tang, Ke; Emmerich, Michael T. M.
- A decision support system for corporations cybersecurity managementPublication . Roldan-Molina, Gabriela; Almache-Cueva, Mario; Silva-Rabadão, Carlos; Yevseyeva, Iryna; Basto-Fernandes, VitorThis paper presents ongoing work on a decision aiding software intended to support cyber risks and cyber threats analysis of an information and communications technological infrastructure. The software will help corporations Chief Information Security Officers on cyber security risk analysis, decision-making, prevention measures and risk strategies for the infrastructure and information assets protection.
- An EAI Based Integration Solution for Science and Research Outcomes Information ManagementPublication . Sequeira, Fernando Rosa; Frantz, Rafael Z.; Yevseyeva, Iryna; Emmerich, Michael T.M.; Basto-Fernandes, VitorIn this paper we present an Enterprise Application Integration (EAI) based proposal for research outcomes information management. The proposal is contextualized in terms of national and international science and research outcomes information management, corresponding supporting information systems and ecosystems. Information systems interoperability problems, approaches, technologies and tools are presented and applied to the research outcomes information management case. A business and technological perspective is provided, including the conceptual analysis and modelling, an integration solution based in a Domain-Specific Language (DSL) and the orchestration engine to execute the proposed solution. For illustrative purposes, the role and information system needs of a research unit is assumed as the representative case.
- Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput OptimizationPublication . Ruano-Ordás, David; Basto-Fernandes, Vitor; Yevseyeva, Iryna; Méndez, José RamónThis paper presents an evolutionary multi-objective optimization problem formulation for the anti-spam filtering problem, addressing both the classification quality criteria (False Positive and False Negative error rates) and email messages classification time (minimization). This approach is compared to single objective problem formulations found in the literature, and its advantages for decision support and flexible/adaptive anti-spam filtering configuration is demonstrated. A study is performed using the Wirebrush4SPAM framework anti-spam filtering and the SpamAssassin email dataset. The NSGA-II evolutionary multi-objective optimization algorithm was applied for the purpose of validating and demonstrating the adoption of this novel approach to the anti-spam filtering optimization problem, formulated from the multi-objective optimization perspective. The results obtained from the experiments demonstrated that this optimization strategy allows the decision maker (anti-spam filtering system administrator) to select among a set of optimal and flexible filter configuration alternatives with respect to classification quality and classification efficiency.
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