Titlebook: ICT Innovations 2009; Danco Davcev,Jorge Marx Gómez Conference proceedings 2010 Springer-Verlag Berlin Heidelberg 2010 Artificial Intellig

恰当

书目名称ICT Innovations 2009影响因子(影响力)




书目名称ICT Innovations 2009影响因子(影响力)学科排名




书目名称ICT Innovations 2009网络公开度




书目名称ICT Innovations 2009网络公开度学科排名




书目名称ICT Innovations 2009被引频次




书目名称ICT Innovations 2009被引频次学科排名




书目名称ICT Innovations 2009年度引用




书目名称ICT Innovations 2009年度引用学科排名




书目名称ICT Innovations 2009读者反馈




书目名称ICT Innovations 2009读者反馈学科排名

Rct393

Ablation

Compensatory Fuzzy Ontology for the formal representation of uncertainty. We present in this paper the formal definition of “Compensatory Fuzzy Ontologies” and attempt to bring to light the need for enhanced knowledge representation systems, using the advantages of this approach, which would increase the effectiveness of using knowledge in the field of decision making.

繁忙

Feigned

Position Estimation of Mobile Robots Using Unsupervised Learning Algorithmsto generate a set of controls to reach a desired destination. For the learning of the environment, two unsupervised algorithms FuzzyART neural network and GNG network were used. The approach was tested for its ability to recognize previously learnt positions. Both algorithms that were used were compared for their precision.

砍伐

ons 2009. The ICT Innovations conference is the primary scientific action of the Macedonian Society on Information and Communication Technologies (ICT-ACT). It promotes the publication of scientific results of the international community related to innovative fundamental and applied research in ICT.

airborne

Applying Bagging Techniques to the SA Tabu Miner Rule Induction Algorithmeral bootstrap methodologies were applied to SA Tabu Miner, including reducing repetition of instances, forcing repetition of instances not to exceed two, using different percentages of the original basic training set. Various experimental approaches and parameters yielded different results on the compared datasets.

处理

Protein Classification Based on 3D Structures and Fractal Featuresh achieves 86% classification accuracy with applying fractal filter, and 92% without fractal filter. It is shown that fractal filter significantly shorten the classification time. Our system is faster (seconds) than DALI system (minutes, hours, days), and we still get satisfactory results.

结束

Aggrandize