41 research outputs found
Hybridising heuristics within an estimation distribution algorithm for examination timetabling
This paper presents a hybrid hyper-heuristic approach based on estimation distribution algorithms. The main motivation is to raise the level of generality for search methodologies. The objective of the hyper-heuristic is to produce solutions of acceptable quality for a number of optimisation problems. In this work, we demonstrate the generality through experimental results for different variants of exam timetabling problems. The hyper-heuristic represents an automated constructive method that searches for heuristic choices from a given set of low-level heuristics based only on non-domain-specific knowledge. The high-level search methodology is based on a simple estimation distribution algorithm. It is capable of guiding the search to select appropriate heuristics in different problem solving situations. The probability distribution of low-level heuristics at different stages of solution construction can be used to measure their effectiveness and possibly help to facilitate more intelligent hyper-heuristic search methods
A New Neural Network Based Construction Heuristic for the Examination Timetabling Problem
Fuzzy multiple heuristic orderings for course timetabling
In this paper, we address the issue of ordering events by simultaneously con- sidering three separate heuristics using fuzzy methods. Combinations of the fol- lowing three heuristic orderings are em- ployed: largest degree, saturation degree and largest enrollment. The fuzzy weight of an event is used to represent how difficult it is to schedule. The decreasingly ordered events are sequentially chosen to be assigned to the last slot with least penalty cost value while the feasibility of the timetable is maintained throughout the process. Unscheduling and reschedul- ing events is performed until all events are scheduled. The proposed algorithm has been tested on 11 benchmark data sets of course timetabling problems and the re- sults show that this approach can produce good quality solutions with low require- ments for rescheduling. Moreover, there is signi?cant potential to extend the ap- proach further by including a larger range of criteria
An improved model-based technique for generating test scenarios from UML class diagrams
The foundation of any software testing process is test scenario generation. This is because it forecasts the expected output of a system under development by extracting the artifacts expressed in any of the Unified Modeling Language (UML) diagrams, which are eventually used as the basis for software testing. Class diagrams are UML structural diagrams that describe a system by displaying its classes, attributes, and the relationships between them. Existing class diagram-based test scenario generation techniques only extract data variables and functions, which leads to incomprehensible or vague test scenarios. Consequently, this chapter aims to develop an improved technique that automatically generates test scenarios by reading, extracting, and interpreting the sets of objects that share attributes, operations, relationships, and semantics in a class diagram. From the performance evaluation, the proposed modelbased technique is efficiently able to read, interpret, and generate scenarios from all the descriptive links of a class diagram
Dirasah Islamiyah 1 Pengantar Studi Al-Qur'an, Al-Hadits Fiqh Dan Pranata Sosial
ilus, xi, 130 hlm, 20.5 c
A unified approach for unconstrained off-angle iris recognition
Improving the performance of non-idealistic iris recognition has recently become one of the main focus in iris biometric research. In real-world iris image acquisitions, it is common and unavoidable to capture off-angle iris images. Such off-angle iris images are categorized as non-idealistic because they substantially degrade the performance of iris recognition. In this paper, we present a unified framework designed to improve off-angle iris recognition performance. We propose combination of least square ellipse fitting (LSEF) technique and the geometric calibration (GC) technique for the iris segmentation. For off-angle images, the improper location of iris and pupil interferes with the ability to effectively segment the inner boundary and outer boundary of the iris image. With the proposed techniques, inner and outer boundaries are fitted iteratively. For feature extraction, we propose a NeuWave Network (inspired by the Haar wavelet decomposition and neural network). The iris features are represented using the wavelet coefficients. Each different angle of the iris have its own significant coefficient and these coefficient, with a set of weights, then forms the iris template. The approach is evaluated based on recognition accuracy measured by the false rejection, false acceptance rate, and decidability index. We evaluate the algorithms with WVU-IBIDC datasets
Clustering Alkire foster-oriented quantification in measuring multidimensional poverty indicators by using intelligent adaptive neural fuzzy inference systems
Malaysia is a developing country which relies on the monetary approach when it comes to poverty measurement. The current monetary approach is simpler to measure; however, it is insensitive towards changes of the poor in multiple dimensions especially in urban area. Based on household survey data on urban province in Malaysia, this study proposes on a multidimensional poverty measurement framework, which predicts on the prominent deprived indicators based on multidimensional urban poor measurement, replacing the conventional money-metric measure. This study highlights on integration between Alkire-Foster approaches in quantification of multidimensional urban poor with Adaptive Neural Fuzzy Inference Systems (ANFIS). By addressing the deprived indicator in urban area, the combination of Alkire Foster and ANFIS approach could efficiently resolve on the issue of misfit urban poor in the country. In this study, Alkire Foster approach is proven to have promising results in improving the determination of the urban poor in Malaysia. In future, this study aims in addressing the particular combination of indicator that causes the urban poverty in Malaysia