454 research outputs found
AN ALGORITHM OF FUZZY INFERENCE SYSTEM FOR HUMAN RESOURCES SELECTION TOOLS
This article offers an original Human Resources selection procedure based on Mamdani fuzzy inference system (FIS) dedicated to compute multiple results each from different type of analyzing criterions. The modeling and information analysis of the FIS are developed to draw a general conclusion from several results each produced by Human Resources selection basic criterion. Simulation experiments are carried out in MATLAB environment
Recommended from our members
The foundation of capability modelling: A study of the impact and utilisation of human resources
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This research aims at finding a foundation for assessment of capabilities and applying the concept in a human resource selection. The research identifies a common ground for assessing individualsâ applied capability in a given job based on literature review of various disciplines in engineering, human sciences and economics. A set of criteria is found to be common and appropriate to be used as the basis of this assessment. Applied Capability is then described in this research as the impact of the person in fulfilling job requirements and also their level of usage from their resources with regards to the identified criteria. In other words how their available resources (abilities, skills, value sets, personal attributes and previous performance records) can be used in completing a job. Translation of the personâs resources and task requirements using the proposed criteria is done through a novel algorithm and two prevalent statistical inference techniques (OLS regression and Fuzzy) are used to estimate quantitative levels of impact and utilisation. A survey on post graduate students is conducted to estimate their applied capabilities in a given job. Moreover, expert academics are surveyed on their views on key applied capability assessment criteria, and how different levels of match between job requirement and personâs resources in those criteria might affect the impact levels. The results from both surveys were mathematically modelled and the predictive ability of the conceptual and mathematical developments were compared and further contrasted with the observed data. The models were tested for robustness using experimental data and the results for both estimation methods in both surveys are close to one another with the regression models being closer to observations. It is believed that this research has provided sound conceptual and mathematical platforms which can satisfactorily predict individualsâ applied capability in a given job.
This research has contributed to the current knowledge and practice by a) providing a comparison of capability definitions and uses in different disciplines, b) defining criteria for applied capability assessment, c) developing an algorithm to capture applied capabilities, d) quantification of an existing parallel model and finally e) estimating impact and utilisation indices using mathematical methods
The foundation of capability modelling : a study of the impact and utilisation of human resources
This research aims at finding a foundation for assessment of capabilities and applying the concept in a human resource selection. The research identifies a common ground for assessing individualsâ applied capability in a given job based on literature review of various disciplines in engineering, human sciences and economics. A set of criteria is found to be common and appropriate to be used as the basis of this assessment. Applied Capability is then described in this research as the impact of the person in fulfilling job requirements and also their level of usage from their resources with regards to the identified criteria. In other words how their available resources (abilities, skills, value sets, personal attributes and previous performance records) can be used in completing a job. Translation of the personâs resources and task requirements using the proposed criteria is done through a novel algorithm and two prevalent statistical inference techniques (OLS regression and Fuzzy) are used to estimate quantitative levels of impact and utilisation. A survey on post graduate students is conducted to estimate their applied capabilities in a given job. Moreover, expert academics are surveyed on their views on key applied capability assessment criteria, and how different levels of match between job requirement and personâs resources in those criteria might affect the impact levels. The results from both surveys were mathematically modelled and the predictive ability of the conceptual and mathematical developments were compared and further contrasted with the observed data. The models were tested for robustness using experimental data and the results for both estimation methods in both surveys are close to one another with the regression models being closer to observations. It is believed that this research has provided sound conceptual and mathematical platforms which can satisfactorily predict individualsâ applied capability in a given job. This research has contributed to the current knowledge and practice by a) providing a comparison of capability definitions and uses in different disciplines, b) defining criteria for applied capability assessment, c) developing an algorithm to capture applied capabilities, d) quantification of an existing parallel model and finally e) estimating impact and utilisation indices using mathematical methods.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Fuzzy Logic
The capability of Fuzzy Logic in the development of emerging technologies is introduced in this book. The book consists of sixteen chapters showing various applications in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems. This book is a major reference source for all those concerned with applied intelligent systems. The intended readers are researchers, engineers, medical practitioners, and graduate students interested in fuzzy logic systems
INTERVAL TYPE-2 FUZZY MODEL FOR CUSTOMER COMPLAINT HANDLING
Complaint management system (CMS) has become increasingly important for organizations, businesses, and government in Malaysia. The interaction between customers and business provider based on complaints which referring to perceptions and wording involves uncertainties and not an easy task in complaint handling process to rank the complaint
Decision Support Systems for Risk Assessment in Credit Operations Against Collateral
With the global economic crisis, which reached its peak in the second half of 2008, and
before a market shaken by economic instability, financial institutions have taken steps to protect
the banksâ default risks, which had an impact directly in the form of analysis in credit institutions
to individuals and to corporate entities. To mitigate the risk of banks in credit operations, most
banks use a graded scale of customer risk, which determines the provision that banks must
do according to the default risk levels in each credit transaction. The credit analysis involves
the ability to make a credit decision inside a scenario of uncertainty and constant changes and
incomplete transformations. This ability depends on the capacity to logically analyze situations,
often complex and reach a clear conclusion, practical and practicable to implement.
Credit Scoring models are used to predict the probability of a customer proposing to
credit to become in default at any given time, based on his personal and financial information
that may influence the ability of the client to pay the debt. This estimated probability, called the
score, is an estimate of the risk of default of a customer in a given period. This increased concern
has been in no small part caused by the weaknesses of existing risk management techniques
that have been revealed by the recent financial crisis and the growing demand for consumer
credit.The constant change affects several banking sections because it prevents the ability to
investigate the data that is produced and stored in computers that are too often dependent on
manual techniques.
Among the many alternatives used in the world to balance this risk, the provision of
guarantees stands out of guarantees in the formalization of credit agreements. In theory, the
collateral does not ensure the credit return, as it is not computed as payment of the obligation
within the project. There is also the fact that it will only be successful if triggered, which involves
the legal area of the banking institution. The truth is, collateral is a mitigating element
of credit risk. Collaterals are divided into two types, an individual guarantee (sponsor) and the
asset guarantee (fiduciary). Both aim to increase security in credit operations, as an payment
alternative to the holder of credit provided to the lender, if possible, unable to meet its obligations
on time. For the creditor, it generates liquidity security from the receiving operation. The
measurement of credit recoverability is a system that evaluates the efficiency of the collateral
invested return mechanism.
In an attempt to identify the sufficiency of collateral in credit operations, this thesis
presents an assessment of smart classifiers that uses contextual information to assess whether
collaterals provide for the recovery of credit granted in the decision-making process before
the credit transaction become insolvent. The results observed when compared with other approaches
in the literature and the comparative analysis of the most relevant artificial intelligence
solutions, considering the classifiers that use guarantees as a parameter to calculate the
risk contribute to the advance of the state of the art advance, increasing the commitment to
the financial institutions.Com a crise econĂŽmica global, que atingiu seu auge no segundo semestre de 2008, e diante
de um mercado abalado pela instabilidade econÎmica, as instituiçÔes financeiras tomaram
medidas para proteger os riscos de inadimplĂȘncia dos bancos, medidas que impactavam diretamente
na forma de anĂĄlise nas instituiçÔes de crĂ©dito para pessoas fĂsicas e jurĂdicas. Para
mitigar o risco dos bancos nas operaçÔes de crédito, a maioria destas instituiçÔes utiliza uma
escala graduada de risco do cliente, que determina a provisĂŁo que os bancos devem fazer de
acordo com os nĂveis de risco padrĂŁo em cada transação de crĂ©dito. A anĂĄlise de crĂ©dito envolve
a capacidade de tomar uma decisão de crédito dentro de um cenårio de incerteza e mudanças
constantes e transformaçÔes incompletas. Essa aptidão depende da capacidade de analisar situaçÔes
lĂłgicas, geralmente complexas e de chegar a uma conclusĂŁo clara, prĂĄtica e praticĂĄvel
de implementar.
Os modelos de Credit Score sĂŁo usados para prever a probabilidade de um cliente
propor crédito e tornar-se inadimplente a qualquer momento, com base em suas informaçÔes
pessoais e financeiras que podem influenciar a capacidade do cliente de pagar a dĂvida. Essa
probabilidade estimada, denominada pontuação, Ă© uma estimativa do risco de inadimplĂȘncia de
um cliente em um determinado perĂodo. A mudança constante afeta vĂĄrias seçÔes bancĂĄrias,
pois impede a capacidade de investigar os dados que sĂŁo produzidos e armazenados em computadores
que frequentemente dependem de técnicas manuais.
Entre as inĂșmeras alternativas utilizadas no mundo para equilibrar esse risco, destacase
o aporte de garantias na formalização dos contratos de crédito. Em tese, a garantia não
âgaranteâ o retorno do crĂ©dito, jĂĄ que nĂŁo Ă© computada como pagamento da obrigação dentro do
projeto. Tem-se ainda, o fato de que esta sĂł terĂĄ algum ĂȘxito se acionada, o que envolve a ĂĄrea
jurĂdica da instituição bancĂĄria. A verdade Ă© que, a garantia Ă© um elemento mitigador do risco
de crédito. As garantias são divididas em dois tipos, uma garantia individual (patrocinadora) e
a garantia do ativo (fiduciårio). Ambos visam aumentar a segurança nas operaçÔes de crédito,
como uma alternativa de pagamento ao titular do crĂ©dito fornecido ao credor, se possĂvel, nĂŁo
puder cumprir suas obrigaçÔes no prazo. Para o credor, gera segurança de liquidez a partir da
operação de recebimento. A mensuração da recuperabilidade do crédito é uma sistemåtica que
avalia a eficiĂȘncia do mecanismo de retorno do capital investido em garantias.
Para tentar identificar a suficiĂȘncia das garantias nas operaçÔes de crĂ©dito, esta tese
apresenta uma avaliação dos classificadores inteligentes que utiliza informaçÔes contextuais
para avaliar se as garantias permitem prever a recuperação de crédito concedido no processo de
tomada de decisão antes que a operação de crédito entre em default. Os resultados observados
quando comparados com outras abordagens existentes na literatura e a anĂĄlise comparativa das
soluçÔes de inteligĂȘncia artificial mais relevantes, mostram que os classificadores que usam
garantias como parùmetro para calcular o risco contribuem para o avanço do estado da arte,
aumentando o comprometimento com as instituiçÔes financeiras
AI-Augmented HRM: Literature review and a proposed multilevel framework for future research.
The research using artificial intelligence (AI) applications in HRM functional areas has gained much traction and a steep surge over the last three years. The extant literature observes that contemporary AI applications have augmented HR functionalities. AI-Augmented HRM HRM(AI) has assumed strategic importance for achieving HRM domain-level outcomes and organisational outcomes for a sustainable competitive advantage. Moreover, there is increasing evidence of literature reviews pertaining to the use of AI applications in different management disciplines (i.e., marketing, supply chain, accounting, hospitality, and education). There is a considerable gap in existing studies regarding a focused, systematic literature review on HRM(AI), specifically for a multilevel framework that can offer research scholars a platform to conduct potential future research. To address this gap, the authors present a systematic literature review (SLR) of 56 articles published in 35 peer-reviewed academic journals from October 1990 to December 2021. The purpose is to analyse the context (i.e., chronological distribution, geographic spread, sector-wise distribution, theories, and methods used) and the theoretical content (key themes) of HRM(AI) research and identify gaps to present a robust multilevel framework for future research. Based upon this SLR, the authors identify noticeable research gaps, mainly stemming from - unequal distribution of previous HRM(AI) research in terms of the smaller number of sector/country-specific studies, absence of sound theoretical base/frameworks, more research on routine HR functions(i.e. recruitment and selection) and significantly less empirical research. We also found minimal research evidence that links HRM(AI) and organisational-level outcomes. To overcome this gap, we propose a multilevel framework that offers a platform for future researchers to draw linkage among diverse variables starting from the contextual level to HRM and organisational level outcomes that eventually enhance operational and financial organisational performance
Strategic Assessment of Organizational Commitment
The concept of organizational commitment has been widely studied over recent decades, yet it remains one of the most challenging concepts in organizational research. While commitment is understood to be highly valuable in todayâs dynamic business environment, its multifaceted nature is not necessarily understood adequately. The purpose of this study was to examine the concept of organizational commitment and its measurement issues within organizations, and to develop a practical evaluation tool for management, which is based on previous scientific research.
First, a theoretical framework discussing organizational commitment and engagement was established. Based on the literature research, three ontologies were developed addressing organizational commitment and engagement, as well as academic engagement. The ontologies were constructed as a synthesis of existing theories. With the help of the ontologies and the created evaluation system, it is possible to better understand these concepts, gain a collective view of the organizationâs current state and vision for the future, and to open a dialogue between members of the organization regarding their development.
The results of the empirical case studies are presented at the end of this thesis, as well as in the attached research papers. The empirical results indicate that, by using these applications, it is possible to gain insights about the respondentsâ feelings and aspirations, which can be used to support effective decision-making and as the basis for creating development actions within the organization.Organisaatiositoutumisen kĂ€sitettĂ€ on tutkittu laajasti kuluneiden vuosikymmenten aikana, kuitenkin se on edelleen yksi organisaatiotutkimuksen haastavimmista kĂ€sitteistĂ€. Sitoutuminen on laajalti ymmĂ€rretty erittĂ€in tĂ€rkeĂ€ksi tĂ€mĂ€n pĂ€ivĂ€n liiketoimintaympĂ€ristössĂ€ mutta sen moniulotteista luonnetta ei yrityksissĂ€ ole vĂ€lttĂ€mĂ€ttĂ€ ymmĂ€rretty riittĂ€vĂ€sti.
TÀmÀn tutkimuksen tavoitteena oli tarkastella organisatorisen sitoutumisen kÀsitettÀ ja sen mittaamisen ongelmallisuutta sekÀ kehittÀÀ aikaisempaan tieteelliseen tutkimukseen perustuva kÀytÀnnön sovellus sitoutumisen tason mÀÀrittÀmiseksi.
Tutkimuksen ensimmÀisessÀ osassa laadittiin organisaatioon sitoutumista kÀsittelevÀ teoreettinen viitekehys, jonka perusteella kehitettiin kolme ontologiaa. Ontologiat kÀsittelevÀt organisaation sitoutumista eri nÀkökulmista sekÀ opiskelijoiden akateemista sitoutumista. Ontologioiden sekÀ laaditun arviointijÀrjestelmÀn avulla on mahdollista ymmÀrtÀÀ sitoutumiseen liittyviÀ kÀsitteitÀ, saada yhteinen nÀkemys organisaation nykytilasta ja tulevaisuuden nÀkemyksestÀ sekÀ löytÀÀ mahdollisia kehityskohteita. Empiiristen case-tutkimusten tuloksia on esitetty tÀmÀn työn loppuosassa sekÀ liitteenÀ olevissa tutkimusartikkeleissa. Tulokset osoittavat, ettÀ laadittujen sovellusten avulla on mahdollista saada tietoa vastaajien tuntemuksista ja pyrkimyksistÀ. TÀtÀ tietoa voidaan hyödyntÀÀ pÀÀtöksenteon tukena sekÀ perustana kehitystoimien luomiselle.fi=vertaisarvioitu|en=peerReviewed
Multi-Agent based Intelligent Decision Support Systems for Cancer Classification
There is evidence that early detection of cancer diseases can improve the treatment and increase
the survival rate of patients. This paper presents an efficient CAD system for cancer diseases diagnosis
by
gene
expression
profiles
of
DNA
microarray
datasets.
The proposed CAD system combines
Intelligent Decision Support System (IDSS) and Multi-Agent (MA) system. The IDSS represents the
backbone of the entire CAD system. It consists of two main phases; feature selection/reduction
phase and a classification phase. In the feature selection/reduction phase, eight diverse methods are
developed. While, in the classification phase, three evolutionary machine learning algorithms are
employed. On the other hand, the MA system manages the entire operation of the CAD system. It
first initializes several IDSSs (exactly 24 IDSSs) with the aid of mobile agents and then directs the generated
IDSSs
to
run
concurrently
on
the
input
dataset.
Finally,
a
master
agent
selects
the
best
classification,
as
the
final
report,
based
on
the
best
classification
accuracy
returned
from
the
24
IDSSs The proposed CAD system is implemented in JAVA, and evaluated by using three microarray datasets
including; Leukemia, Colon tumor, and Lung cancer. The system is able to classify different types of
cancer diseases accurately in a very short time. This is because the MA system invokes 24 different
IDSS to classify the diseases concurrently in parallel processing manner before taking the decision of
the best classification result
- âŠ