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With the advent of big data era, complex optimization problems with many objectives and large numbers of decision variables are constantly emerging. Traditional research about multi-objective particle swarm optimization (PSO) focuses on multi-objective optimization problems (MOPs) with small numbers of variables and less than four objectives. At present, MOPs with large numbers of variables and many...
This paper proposes a new process recommendation approach on supplying some related processes for choice when users start their business. The process recommendation model is based on the association rules and transaction context, and it aims at mining the potential associated relationship between processes, which can help organizations and users to improve their work efficiency. In this paper, we...
Workflow management systems (WFMS) facilitate the routine operation of business processes and gain popularity in recent years. To ensure the correctness of business process specification and execution, model verification (especially structure verification) must be conducted so that we can identify any violations and consequently take proper action to remove them in time. However, little progress has...
Production system which accepts the facts and draws conclusions by repeatedly matching facts with rules plays an important role of improving the business by providing agility and flexibility. However, rule matching in production is badly time-consuming, and single computer limits the improvement for current matching algorithm. To address these problems, we proposed a MapReduce-based architecture to...
Shape context algorithm is a recently proposed good method for object recognition. It is robust under small geometrical distortions and occlusion, invariant under scaling, translation, and change of illumination. However, because of its computational complexity, this algorithm is not suitable for online recognition. In this paper, we proposed an improved shape context algorithm which introduces an...
Single pattern matching algorithm used in intrusion detection system is efficient when there are not so many patterns to process. However, if there are a large number of patterns to process, it will be less efficient. In order to solve that problem, this paper introduces the set-based multi-pattern matching algorithm application for intrusion detection. Experimental results show that the algorithm...
Template matching is an effective approach for pedestrian detection. In order to achieve real-time and accurate detection, how to obtain a suitable representative template set is still an open problem due to the large variety of pedestrian shape. This paper introduced a representative template generation method for a template matching based pedestrian detection system (PDS). Based on nonlinear manifold...
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