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This paper shows the development and use of a hybrid algorithm of machine learning for the missing values predict task, with this task that is carried out while the data preprocessing phase. Firstly, we go through the problem to solve, which is pointed to the study and analysis of different techniques for the missing values predict in order to suggest a hybrid technique as a product of this research for the task and link it to the OLAP (On-Line Analytical Processing) technology. Then, justifying the research methodology (scientific descriptive - probing) applied in this project. The techniques review was carried out filling out the missing values; based on the techniques proof and the study cases, k-Nearest Neighbors algorithms and artificial neural networks were selected and a hybrid technique (KMediaSom) was suggested, applied to a synthetic data set and a real one, coming from a OLAP; for the algorithms implementation was used Matlab. Right away, the analysis and results are set out in order to specify its applicability about efficacy and time complexity. Results are suitable as for the synthetic data set as for the real one; according to the test signs achieved. Finally, the conclusions, where it i's proved that the technique or hybrid algorithms generate better results than the techniques used by separately. [ABSTRACT FROM AUTHOR]

The motion estimation is an essential block in the prediction stage of the H.264/AVC video compression standard, which is crucial for obtaining an effective coding rate. Different algorithms have been proposed in the literature to optimize the architecture of this block, since it requires a long execution time and a significant number of computational resources. Traditional strategies based on the search on each block allow ensuring high quality but are inappropriate in terms of computational efficiency; other methods based on search by regions reduce the processing load, but do not guarantee a good quality. In this paper it is implemented a multilayer perceptron neural network with supervised backpropagation learning algorithm which allows making the estimation. [ABSTRACT FROM AUTHOR]

This paper described the problem of path-planning in mobile robots in a partially structured environment. The work was divided in three parts: design of a mechatronic system, denominated Robot IO, study of advantages and disadvantages of three path-planning algorithms: neural nets, genetic algorithms and fuzzy logic, and implementation of algorithms that allow to identify the workspace where IO moves. [ABSTRACT FROM AUTHOR]