Selecting an effective method for combining the votes of base inducers in a multiclassifier system can have a significant impact on the system’s overall classification accuracy. Some methods cannot even achieve as high a classification accuracy as the most accurate base classifier. To address this issue, we present the strategy of aggregate certainty estimators, which uses multiple measures to ...

Case-Based Reasoning systems usually retrieve cases using a similarity function based on K-NN or some derivatives. These functions are sensitive to irrelevant or noisy features. Weighting methods are used to extract the most important information present in the knowledge and determine the importance of each feature. However, this knowledge, can also be incorrect, redundant and inconsistent. In ...

Although simple additive weighting method (SAW) is the most popular approach for classical multiple attribute decision making (MADM), it is not practical any more if information is fuzzy. The existing methods of Fuzzy Simple Additive Weighting method (FSAW) apply defuzzification which distorts fuzzy numbers. Furthermore, most of the methods usually require lengthy and laborious manipulations. I...

today, in the rangeland management science and determination of rangecapacity, accurate and true information about range production is crucial. in fact, rangeproduction is considered as a basis for range management. the aim of this study was tocompare different methods for the estimation of forage production with four samplingmethods in the rangelands of kurdistan province, iran. the sampling m...

Multi-atlas based segmentation has been applied widely in medical image analysis. For label fusion, previous studies show that image similarity-based local weighting techniques produce the most accurate results. However, these methods ignore the correlations between results produced by different atlases. Furthermore, they rely on pre-selected weighting models and ad hoc methods to choose model ...

This article addresses weighting and partitioning, in complex reinforcement learning tasks, with the aim of facilitating learning. The article presents some ideas regarding weighting of multiple agents and extends them into partitioning an input/state space into multiple regions with differential weighting in these regions, to exploit differential characteristics of regions and differential cha...

We proposed Wireless LAN (WLAN) localization method that enhances database construction based on weighting factor and analyses the characteristic of the WLAN received signals. The weighting factor plays a key role as it determines the importance of Received Signal Strength Indication (RSSI) value from number of received signals (frequency). The fingerprint method is the most widely used method ...

Weare pleased to present this special issue ofDiscrete AppliedMathematics, which is devoted to the 12th Cologne-Twente Workshop on Graphs and Combinatorial Optimization (CTW 2013), held at the University of Twente, Enschede, The Netherlands, between May 21 and May 23, 2013. More than 80 scientists from all over the world attended the workshop, and we take this opportunity to thank all CTW 2013 ...

The height assignment of atmospheric motion vectors (AMV) is still an open issue. From the numerous height assignment techniques, each retrieval method has its own characteristics. The presented stereophotogrammetric method has the advantage that it is only dependent on the geometry and therefore offers a completely independent height retrieval compared to the other methods. As polar-orbiting i...