scholarly journals An Intelligent System for Structural Analysis-Based Design Improvements

10.14311/1059 ◽  
2008 ◽  
Vol 48 (6) ◽  
Author(s):  
M. Novak ◽  
B. Dolšak
Keyword(s):  
Structural Analysis ◽  
Intelligent System ◽  
New Products ◽  
Research Work ◽  
Educational Tool ◽  
Intelligent Decision Support System ◽  
Design Changes ◽  
Intelligent Decision ◽  
Intelligent Decision Support ◽  
Prior Stress

The goal of the research work presented in this paper was to collect, organize, and write the knowledge and experience about structural analysis-based design improvements into a knowledge base for a consultative advisory intelligent decision support system. The prototype of the system presented proposes possible design changes that should be taken into consideration to improve the design candidate according to the results of a prior stress-strain or thermal analysis. The system can be applied either in the design of new products or as an educational tool. 

An intelligent decision support system for the design of new products

2018 ◽  
Author(s):  
J. F. Figueroa Pérez ◽  
J. C. Leyva López ◽  
L. C. Santillán Hernández ◽  
E. O. Pérez Contreras
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
New Products ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Intelligent Decision Support

scholarly journals Intelligent decision support system approach for predicting the performance of students based on three-level machine learning technique

2021 ◽  
Vol 30 (1) ◽  
pp. 739-749
Author(s):  
Sohaib Latif ◽  
Fang XianWen ◽  
Li-li Wang
Keyword(s):  
Machine Learning ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Research Work ◽  
Individual Student ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
The Individual ◽  
Intelligent Decision Support

Abstract In this research work, a user-friendly decision support framework is developed to analyze the behavior of Pakistani students in academics. The purpose of this article is to analyze the performance of the Pakistani students using an intelligent decision support system (DSS) based on the three-level machine learning (ML) technique. The neural network used a three-level classifier approach for the prediction of Pakistani student achievement. A self-recorded dataset of 1,011 respondents of graduate students of English and Physics courses are used. The ten interviews along with ten questions were conducted to determine the perception of the individual student. The chi-squared ( χ ) \left(\chi ) test was applied to test statistical significancy of the questionnaire. The statistical calculations and computation of data were performed by using the statistical package of IBMM SPSS version 21.0. The seven different algorithms were tested to improve the data classification. The Java-based environment was used for the development of numerous prediction classifiers. C4.5 algorithm shows the finest accuracy, whereas Naïve Bayes (NB) algorithm shows the least. The results depict that the classifier’s efficiency was improved by using a three-level proposed scheme from 83.2% to 88.8%. This prediction has shown remarkable results when compared with the individual level classifier technique of ML. This improvement in the accuracy of DSSs is used to identify more efficiently the gray areas in the education stratum of Pakistan. This will pave a path for making policies in the higher education system of Pakistan. The presented framework can be deployed on different platforms under numerous operating systems.

scholarly journals Intelligent Decision Support System

2021 ◽  
Author(s):  
Moruf Akin Adebowale
Keyword(s):  
Research Work ◽  
Healthcare Providers ◽  
Practical Implementation ◽  
Intelligent Decision Support System ◽  
Phishing Attacks ◽  
Intelligent Decision ◽  
Feature Based ◽  
Novel Strategy ◽  
Intelligent Decision Support ◽  
Phishing Detection

A phishing attack is one of the most common forms of cybercrime worldwide. In recent years, phishing attacks have continued to escalate in severity, frequency and impact. Globally, the attacks cause billions of dollars of losses each year. Cybercriminals use phishing for various illicit activities such as personal identity theft and fraud, and to perpetrate sophisticated corporate-level attacks against financial institutions, healthcare providers, government agencies and businesses. Several solutions using various methodologies have been proposed in the literature to counter web-phishing threats. This research work adopts a novel strategy to the detection and prevention of website phishing attacks, with a practical implementation through development towards a browser toolbar add-in. The IPDS is shown to be highly effective both in the detection of phishing attacks and in the identification of fake websites. Experimental results show that approach using the CNN + LSTM has a 93.28% accuracy with an average detection time of 25 seconds, whilst the approach has a slightly lower accuracy. These times are within typical times for loading a web page which makes toolbar integration into a browser a practical option for website phishing detection in real time. The results of this development are compared with previous work and demonstrate both better or similar detection performance. This is the first work that considers how best to integrate images, text and frames in a hybrid feature-based solution for a phishing detection scheme.

scholarly journals An Intelligent System for Allocating Times to the Main Activities of Managers

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 104
Author(s):  
Efrain Solares ◽  
Liliana Guerrero ◽  
Alberto Aguilera ◽  
Juana Hernández ◽  
Sandra Rodríguez ◽  
...  
Keyword(s):  
Decision Support ◽  
Time Allocation ◽  
Intelligent System ◽  
State Of The Art ◽  
Final Decision ◽  
Intelligent Decision Support System ◽  
Novel Approach ◽  
Intelligent Decision ◽  
Intelligent Decision Support

Correctly allocating times to the main activities of a manager is a crucial task that directly affects the possibility of success for any company. Decision support based on state-of-the-art methods can lead to better performance in this activity. However, allocating times to managerial activities is not straightforward; the decision support should provide a flexible recommendation so the manager can make a final decision while ensuring robustness. This paper describes and assesses a novel approach where a search for the best distribution of the manager’s time is performed by an intelligent decision support system. The approach consists of eliciting manager preferences to define the value of the manager’s main activities and, by using a portfolio-like optimization based on differential evolution, obtaining the best time allocation. Aiming at applicability in practical scenarios, the approach can deal with many activities, group decisions, cope with imprecision, vagueness, ill-determination, and other types of uncertainty. We present evidence of the approach’s applicability exploiting a real case study with the participation of several managers. The approach is assessed through the satisfaction level of each manager.

INTELLIGENT DECISION SUPPORT SYSTEM FOR DRUG SELECTION

2019 ◽  
Vol 21 (1) ◽  
pp. 16-22
Author(s):  
M. Yu. Tiahunova ◽  
◽  
N. O. Ilina ◽  
T. V. Holub ◽  
◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Drug Selection ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Intelligent Decision Support

Research on intelligent decision support system of modern agricultural logistic

2010 ◽  
Vol 36 (3) ◽  
pp. 363-366
Author(s):  
Jia-wen PENG ◽  
Jia-hong PENG ◽  
Zhan-sheng BAI ◽  
Xi-lin YU
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Intelligent Decision Support

An Intelligent Decision Support System for Workforce Forecast

2011 ◽  
Author(s):  
Hung-da Wan ◽  
Fengshan F. Chen ◽  
Glenn W. Kuriger
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Intelligent Decision Support

scholarly journals Or-Based Intelligent Decision Support System for E-Commerce

2021 ◽  
Vol 16 (4) ◽  
pp. 1150-1164
Author(s):  
Ke Zong ◽  
Yuan Yuan ◽  
Carlos Enrique Montenegro-Marin ◽  
Seifedine Nimer Kadry
Keyword(s):  
Information Society ◽  
It Professionals ◽  
Key Factors ◽  
Medium Term ◽  
Web Based ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Mechanical Quality ◽  
Fuzzy Logic Theory ◽  
Intelligent Decision Support

Aim: This paper aims to analyze, prepare, and review the general guidelines and rules that govern the development of key factors influencing the enhancement of emotionally supportive networks and selection models using fuzzy logic theory. The researchers have identified eight important components of the information society (IS), representing the computerized economy’s growth to explain a realistic framework for medium-term gauges and proposals. Materials and methods: A discrete-nonstop opportunity paradigm portrays the creation of the general framework, in which the mutual effects of each of the components are spoken to models within the state-space. The software’s mechanical quality offers improvement displayed along these lines that may indicate future interest to programing suppliers. The researchers have given supposed to the developments and interests of information technology (IT) professionals in R&D to provide insightful foundations. For example, this study will demonstrate the development of emotionally supportive networks and recommendations of choices for 3D-web-based businesses and their impact on mechanical advancement, examples of use and social behavior. Results: During an IS/IT foreknowledge undertaking completed in Poland in 2019 and sponsored by the Education Research and Development Foundation ERDF, the results were obtained.

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