An empirical heuristic learning identification algorithm of Ivakhnenko was modified and used to model an environmental system producing high nitrate levels in agricultural drain water in the Corn Belt. The method amou...
详细信息
The Broadband Wireless Access (BWA) technology has been proposed to support different traffic classes with distinct quality of service (QoS) requirements in broadband metropolitan area networks. Therefore, as part of ...
详细信息
The Broadband Wireless Access (BWA) technology has been proposed to support different traffic classes with distinct quality of service (QoS) requirements in broadband metropolitan area networks. Therefore, as part of its specifications, such a system must properly address the combined requirements of wireless communications and multimedia applications. We propose in this paper an extension to the MAC protocol presented in [1, 2], by assigning variable priorities to the network stations sharing access to the communication channel. An analytical model to evaluate the performance of the proposed protocol is also developed and results obtained for the messages waiting times at different stations are presented. In addition, simulation data are used to compare the results obtained from the analytical model presented previously. It is concluded that the proposed variable priority MAC protocol is able to improve channel utilization and provide throughput and queueing delay fairness among the stations in the network.
This monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization and data science. The text situates ...
详细信息
ISBN:
(数字)9783031130786
ISBN:
(纸本)9783031130779;9783031130809
This monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization and data science. The text situates MESP in information theory, as the algorithmic problem of calculating a sub-vector of pre-specificed size from a multivariate Gaussian random vector, so as to maximize Shannon's differential entropy. The text collects and expands on state-of-the-art algorithms for MESP, and addresses its application in the field of environmental monitoring. While MESP is a central optimization problem in the theory of statistical designs (particularly in the area of spatial monitoring), this book largely focuses on the unique challenges of its algorithmic side. From the perspective of mathematical-optimization methodology, MESP is rather unique (a 0/1 nonlinear program having a nonseparable objective function), and the algorithmic techniques employed are highly non-standard. In particular, successful techniques come from several disparate areas within the field of mathematical optimization; for example: convex optimization and duality, semidefinite programming, Lagrangian relaxation, dynamic programming, approximation algorithms, 0/1 optimization (e.g., branch-and-bound), extended formulation, and many aspects of matrix theory. The book is mainly aimed at graduate students and researchers in mathematical optimization and data analytics.
The technical literature regarding model-based testing (MBT) has several techniques with different characteristics and goals available to be applied in software projects. Besides the lack of information regarding thes...
详细信息
The technical literature regarding model-based testing (MBT) has several techniques with different characteristics and goals available to be applied in software projects. Besides the lack of information regarding these techniques, they could be applied together in a software project aiming at improving the testing coverage. However, this decision needs to be carefully analyzed to avoid loss of resources in a software project. Based on this scenario, this paper proposes an approach with the purpose of supporting the unique or combined selection of MBT techniques for a given software project considering two aspects: the adequacy level between MBT techniques and the software project characteristics and impact of more than one MBT technique in some testing process variables. At the end, preliminary results of an experimental evaluation are presented.
BPMN 2.0 is a widely used notation to model business process that has associated tools and techniques to facilitate process management, execution and monitoring. As a result using BPMN to model Software Development Pr...
详细信息
BPMN 2.0 is a widely used notation to model business process that has associated tools and techniques to facilitate process management, execution and monitoring. As a result using BPMN to model Software Development Process (SDP) can leverage on the BPMN's infrastructure to improve SDP quality. Nevertheless, when using BPMN to model Software Processes one can observe the lack of an important feature: means to represent process tailoring. This article introduces the BPMNt, a conservative extension to BPMN that aims at aggregating a tailoring representation mechanism as the one found at SPEM 2.0. BPMNt uses the extensibility classes already present in the BPMN meta-model. Our work also presents an example to illustrate the approach.
In this paper we use execution-driven simulation of a scalable multiprocessor to evaluate the performance of the Andorra-I parallel logic programming system under invalidate and update-based protocols. We use two vers...
详细信息
A system for automatic detection of road damages is essential for logistics management. At the core of the system lies an algorithm for classification of damages. This work intends to establish such an algorithm. In t...
详细信息
Software quality assurance is a crucial process that ensures software products meet specified requirements and quality standards. Achieving an exhaustive test coverage is essential for quality assurance, particularly ...
详细信息
We present two new versions of the fuzzy Markov predictor (FMP) with different dependences among the inputs: first-order and second-order dependences. The FMP is a modification of the hidden Markov model in order to e...
详细信息
We present two new versions of the fuzzy Markov predictor (FMP) with different dependences among the inputs: first-order and second-order dependences. The FMP is a modification of the hidden Markov model in order to enable it to predict numerical values. The FMP can be seen as an extension of the fuzzy Bayes predictor. These hybrid systems are applied to the task of monthly electric load forecasting and successfully compared with one fuzzy system, and two traditional forecasting methods: Box-Jenkins and Winters exponential smoothing.
暂无评论