scholarly journals A decision support system (GesCoN) for managing fertigation in open field vegetable crops. Part I—methodological approach and description of the software

2015 ◽  
Vol 6 ◽  
Author(s):  
Antonio Elia ◽  
Giulia Conversa
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Open Field ◽  
Support System ◽  
Methodological Approach ◽  
Vegetable Crops

Decision support system and weather forecast data for modeling open field vegetable crops evapotranspiration

2021 ◽  
pp. 361-366
Author(s):  
J.S. Rubio-Asensio ◽  
J.M. Ramírez-Cuesta ◽  
J.M. Mirás-Avalos ◽  
J.J. Alarcón ◽  
D.S. Intrigliolo
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Open Field ◽  
Support System ◽  
Weather Forecast ◽  
Vegetable Crops ◽  
Forecast Data

scholarly journals THE PRINCIPLES OF DEVELOPING A MANAGEMENT DECISION SUPPORT SYSTEM FOR SCIENTIFIC EMPLOYEES

2019 ◽  
Vol 4 ◽  
pp. 10-22
Author(s):  
Zarifa Jabrayilova
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Methodological Approach ◽  
Production Model ◽  
Management Decision ◽  
Mental Work ◽  
Functional Scheme ◽  
Characteristic Features

Employees engaged in mental work have become the most valuable assets of any organization in the 21st century. The satisfaction of those involved in mental work requires the provision of objectivity and transparency in their decision-making. This, in turn, entails the development of scientifically motivated decision making mechanisms and scientific-methodological approaches to evaluate their performance based on innovative technologies. The main goal of this article is in development of the scientific and methodological framework for the establishment of a decision support system to manage the employees engaged in mental work and operating in uncertainty. In this regard, initially, the question of evaluating the activities of scientific workers is examined, its characteristic features are determined, and the fuzzy relation model is proposed as a multi-criterion issue formed in uncertainty. Taking into consideration the hierarchical structure of the criteria that allows evaluating the activities of scientific workers, a phased solution method based on an additive aggregation method is proposed. In accordance with the methodology, a functional scheme of the decision support system to manage the scientific personnel is developed. The working principle of each block and the interaction of the blocks are described. The rules for the employees’ management decisions are shown by referring to the knowledge production model. Based on the proposed methodological approach, the implementation phases of the decision support system for the management of the scientific workers of the Institute of Information Technology of ANAS are described. To evaluate the employees’ performance, the tools to collect initial information, evaluate the system of criteria, define their importance coefficients and mathematical descriptions are provided. Some results of the system software are presented. The opportunities of the system based on the proposed methodology to support enterprise mangers to make scientifically justified decisions are provided.

scholarly journals Modeling a fuzzy system for assisting the customer targeting decisions in retail companies

2016 ◽  
Vol 24 (3) ◽  
pp. 259-273
Author(s):  
Angela-Eliza Micu
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy System ◽  
Methodological Approach ◽  
Relevant Information ◽  
Managerial Support ◽  
Fuzzy Algorithms ◽  
Customer Targeting ◽  
Specific Cluster

AbstractThis paper reveals a proposal of a decision support system, enabling retail companies' marketing managers with powerful tools for the customers' portfolios targeting. The innovative methodological approach highlights a fuzzy algorithm based system that captures and computes relevant information about customers, providing a managerial support for making the most effective decisions, according to different degrees of affiliation assigned to customers. The contributions of fuzzy algorithms on targeting decisions reflects the affiliation of customers to a specific cluster, based on computation of the input vectors, income and seniority, leading to performing marketing decisions.

Sign in / Sign up

Export Citation Format

Share Document