LEADER 03973nam 2200829z- 450 001 9910557109603321 005 20231214132900.0 035 $a(CKB)5400000000040951 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68493 035 $a(EXLCZ)995400000000040951 100 $a20202105d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAlgorithms in Decision Support Systems 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 electronic resource (162 p.) 311 $a3-0365-0588-1 311 $a3-0365-0589-X 330 $aThis book aims to provide a new vision of how algorithms are the core of decision support systems (DSSs), which are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. It begins with a discussion of how DSSs will be vital to improving the health of the population. The following article deals with how DSSs can be applied to improve the performance of people doing a specific task, like playing tennis. It continues with a work in which authors apply DSSs to insect pest management, together with an interactive platform for fitting data and carrying out spatial visualization. The next article improves how to reschedule trains whenever disturbances occur, together with an evaluation framework. The final works focus on different relevant areas of DSSs: 1) a comparison of ensemble and dimensionality reduction models based on an entropy criterion; 2) a radar emitter identification method based on semi-supervised and transfer learning; 3) design limitations, errors, and hazards in creating very large-scale DSSs; and 4) efficient rule generation for associative classification. We hope you enjoy all the contents in the book. 606 $aHistory of engineering & technology$2bicssc 610 $asemi-supervised learning 610 $atransfer learning 610 $aradar emitter 610 $adecision support systems 610 $apopulation health management 610 $abig data 610 $amachine learning 610 $adeep learning 610 $apersonalized patient care 610 $aNonlinear regression 610 $ainteractive platform 610 $acomponent-based approach 610 $asoftware architecture 610 $aEclipse-RCP (Rich Client Platform) 610 $aspatial prediction 610 $arule-based expert systems 610 $atennis hitting technique 610 $acomputer algebra systems 610 $aGroebner bases 610 $aBoolean logic 610 $adata envelopment analysis 610 $adimensionality reduction 610 $aensembles 610 $aexhaustive state space search 610 $aentropy 610 $aassociative classification 610 $aclass association rule 610 $avertical data representation 610 $aclassification 610 $aalgorithm evaluation 610 $aparallel algorithms 610 $amulti-objective optimization 610 $atrain rescheduling 610 $avery large-scale decision support systems 610 $avery large-scale data and program cores of information systems 610 $ameta-database 610 $ateleological meta-database 610 $athematic list 610 $aindicators list 610 $acomputational methods list 610 $ageographically dispersed systems 610 $aexternal sources 615 7$aHistory of engineering & technology 700 $aGarcía-Díaz$b Vicente$4edt$01258701 702 $aGarcía-Díaz$b Vicente$4oth 906 $aBOOK 912 $a9910557109603321 996 $aAlgorithms in Decision Support Systems$93036765 997 $aUNINA