The nearness diagram (ND) navigation method is a reactive navigation method used for obstacle avoidance in which five different robot-environment states are defined and five corresponding actions are designed carefully. In the ND+ navigation method, one more robot-environment state is added and all action equations are reformed to both achieve smoother robot motions and reduce manual parameter ...

We explore the idea of automatically crafting a tuning dataset for Statistical Machine Translation (SMT) that makes the hyperparameters of the SMT system more robust with respect to some specific deficiencies of the parameter tuning algorithms. This is an under-explored research direction, which can allow better parameter tuning. In this paper, we achieve this goal by selecting a subset of the ...

In control theory, a controller parameter-tuning method called virtual reference feedback tuning (VRFT) is proposed. VRFT can tune using single experimental data. If be applied to vehicle, the yaw-rate adequately tuned without need for vehicle model. Therefore, this study expands results of realize desired autonomous vehicles. The key point proposed auto-tuning gain-schedule proportional–integr...

Image zooming is one of the current issues of image processing where maintaining the quality and structure of the zoomed image is important. To zoom an image, it is necessary that the extra pixels be placed in the data of the image. Adding the data to the image must be consistent with the texture in the image and not to create artificial blocks. In this study, the required pixels are estimated ...

The runtime of evolutionary algorithms (EAs) depends critically on their parameter settings, which are often problem-specific. Automated schemes for parameter tuning have been developed to alleviate the high costs of manual parameter tuning. Experimental results indicate that self-adaptation, where parameter settings are encoded in the genomes of individuals, can be effective in continuous opti...

The prediction of fill levels in stormwater tanks is an important practical problem in water resource management. In this study state-of-the-art CI methods, i.e. Neural Networks (NN) and Genetic Programming (GP), are compared with respect to their applicability to this problem. The performance of both methods crucially depends on their parametrization. We compare different parameter tuning appr...

The internal competition between categories in the adaptive resonance theory (ART) neural model can be biased by replacing the original choice function by one that contains an attentional tuning parameter under external control. For the same input but different values of the attentional tuning parameter, the network can learn and recall different categories with different degrees of generality,...

Stochastic local search algorithms require finding an appropriate setting of their parameters in order to reach high performance. The parameter tuning approaches that have been proposed in the literature for this task can be classified into two families: on-line and off-line tuning. In this paper, we compare the results we achieved with these two approaches. In particular, we report the results...

A number of image-processing problems can be formulated as optimization problems. The objective function typically contains several terms specifically designed for different purposes. Parameters in front of these terms are used to control the relative weights among them. It is of critical importance to tune these parameters, as quality of the solution depends on their values. Tuning parameter i...