scholarly journals Automatic generation of recommended systems based on qualitative interpretation of monitoring information

2020 ◽  
pp. 50-67
Author(s):  
Эльмира Шамильевна Кремлева ◽  
Александр Павлович Снегуренко ◽  
Светлана Владимировна Новикова ◽  
Наталья Львовна Валитова
Keyword(s):  
Decision Making ◽  
Quantitative Data ◽  
Learning Algorithms ◽  
Automatic Generation ◽  
Computational Experiments ◽  
Verbal Information ◽  
High Quality ◽  
Verbal Form ◽  
Qualitative Interpretation ◽  
Monitoring Information

В статье описаны методы принятия решений на основе алгоритмов интеллектуального обучения, для построения которых используются вербальные элементы. Такие алгоритмы и методы обычно работают в расчетах со строго количественными данными, однако, принимая во внимание человеческий способ восприятия информации в вербальной форме. Человек не принимает непосредственного участия в процессе построения модели, то есть ее структура не зависит от экспертных или иных человеческих мнений, однако качественная вербальная информация (например, элементы нормативных актов, документов, приказов и т. д.) встраивается в алгоритм в закодированной форме. Представлены вычислительные эксперименты. The article describes decision-making methods based on intelligent learning algorithms; for the construction of which verbal elements are used. Such algorithms and methods usually work in calculations with strictly quantitative data; however; taking into account the human way of perceiving information in verbal form. The person does not directly participate in the process of building the model; that is; its structure does not depend on expert or other human opinions; however; high-quality verbal information (for example; elements of regulations; documents; orders; etc.) is embedded in the algorithm in coded form. Computational experiments are presented.

scholarly journals Analyzing Factors Affecting the Sustainability of Land Management Practices in Mecha Woreda, Northwestern Ethiopia

2021 ◽  
Vol 13 (13) ◽  
pp. 7007
Author(s):  
Habtamu Nebere ◽  
Degefa Tolossa ◽  
Amare Bantider
Keyword(s):  
Decision Making ◽  
Land Management ◽  
Land Degradation ◽  
Quantitative Data ◽  
Management Practices ◽  
Short Term ◽  
Factors Affecting ◽  
Decision Making Processes ◽  
Household Heads ◽  
The Impact

In Ethiopia, the practice of land management started three decades ago in order to address the problem of land degradation and to further boost agricultural production. However, the impact of land management practices in curbing land degradation problems and improving the productivity of the agricultural sector is insignificant. Various empirical works have previously identified the determinants of the adoption rate of land management practices. However, the sustainability of land management practices after adoption, and the various factors that control the sustainability of implemented land management practices, are not well addressed. This study analyzed the factors affecting the sustainability of land management practices after implementation in Mecha Woreda, northwestern Ethiopia. The study used 378 sample respondents, selected by a systematic random sampling technique. Binary logistic regression was used to analyze the quantitative data, while the qualitative data were qualitatively and concurrently analyzed with the quantitative data. The sustained supply of fodder from the implemented land management practices, as well as improved cattle breed, increases the sustainability of the implemented land management practices. While lack of agreement in the community, lack of enforcing community bylaws, open cattle grazing, lack of benefits of implemented land management practices, acting as barrier for farming practices, poor participation of household heads during planning and decision-making processes, as well as the lack of short-term benefits, reduce the sustainability of the implemented land management practices. Thus, it is better to allow for the full participation of household heads in planning and decision-making processes to bring practical and visible results in land management practices. In addition, recognizing short-term benefits to compensate the land lost in constructing land management structures must be the strategy in land management practices. Finally, reducing the number of cattle and practicing stall feeding is helpful both for the sustainability of land management practices and the productivity of cattle. In line with this, fast-growing fodder grass species have to be introduced for household heads to grow on land management structures and communal grazing fields for stall feeding.

scholarly journals Systematic literature review of machine learning methods used in the analysis of real-world data for patient-provider decision making

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alan Brnabic ◽  
Lisa M. Hess
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Real World ◽  
Learning Algorithms ◽  
External Validation ◽  
Machine Learning Algorithms ◽  
Learning Methods ◽  
Machine Learning Methods

Abstract Background Machine learning is a broad term encompassing a number of methods that allow the investigator to learn from the data. These methods may permit large real-world databases to be more rapidly translated to applications to inform patient-provider decision making. Methods This systematic literature review was conducted to identify published observational research of employed machine learning to inform decision making at the patient-provider level. The search strategy was implemented and studies meeting eligibility criteria were evaluated by two independent reviewers. Relevant data related to study design, statistical methods and strengths and limitations were identified; study quality was assessed using a modified version of the Luo checklist. Results A total of 34 publications from January 2014 to September 2020 were identified and evaluated for this review. There were diverse methods, statistical packages and approaches used across identified studies. The most common methods included decision tree and random forest approaches. Most studies applied internal validation but only two conducted external validation. Most studies utilized one algorithm, and only eight studies applied multiple machine learning algorithms to the data. Seven items on the Luo checklist failed to be met by more than 50% of published studies. Conclusions A wide variety of approaches, algorithms, statistical software, and validation strategies were employed in the application of machine learning methods to inform patient-provider decision making. There is a need to ensure that multiple machine learning approaches are used, the model selection strategy is clearly defined, and both internal and external validation are necessary to be sure that decisions for patient care are being made with the highest quality evidence. Future work should routinely employ ensemble methods incorporating multiple machine learning algorithms.

scholarly journals Retention or defection? Chinese consumers’ decision-making styles for domestic and global brands

2016 ◽  
Vol 47 (4) ◽  
pp. 83-92
Author(s):  
S. Y. Tzeng ◽  
W. M. Wong
Keyword(s):  
Decision Making ◽  
Marketing Strategies ◽  
High Price ◽  
Chinese Consumers ◽  
High Quality ◽  
Global Brands ◽  
Decision Making Styles ◽  
Managerial Implications ◽  
Foreign Brands ◽  
Sports Shoes

This study explores consumers’ decision-making in terms of intention to switch to foreign brands from domestic brands when purchasing cell phones and sports shoes. A survey of 584 undergraduates in Guangdong, China, shows that domestic brands retain their low quality-conscious, low fashion-and-recreational-conscious and low price-conscious customers and attract low brand-conscious and high choice-confused buyers from foreign brands. Foreign brands typically retain their consumers who are highly conscious of fashion and recreation and keep and draw customers with low choice confusion. High-price-conscious consumers and those who are highly brand-confused will assess foreign and domestic brands when searching for bargains. Regarding managerial implications, local brands should offer products of high quality at low pricesand constantly invest in R&D; foreign brands may expand their customer bases and build interactive brand channels; all companies can retain brand-confused customers with preferential packages and design their marketing strategies based on decision-making styles of their target consumers.

scholarly journals Perception of Country Tourism on Tourism Quality in Lake Toba North Sumatera 2020

2021 ◽  
Vol 4 (1) ◽  
pp. 180-188
Author(s):  
Solahuddin Nasution ◽  
Samerdanta Sinulingga ◽  
Arwina Sufika
Keyword(s):  
Decision Making ◽  
Quantitative Data ◽  
Oil And Gas ◽  
Tourism Industry ◽  
Reliability Test ◽  
Analysis Method ◽  
Tourism Sector ◽  
Quantitative Data Analysis ◽  
North Sumatra ◽  
Oil And Gas Sector

The tourism industry as a foreign exchange earner for the non-oil and gas sector in Indonesia has contributed US $ 16.426 billion in 2018 or around 200 trillion rupiahs. North Sumatra Province is one of the government's priorities in the tourism sector, measured from the construction of Sisingamangaraja XII International Airport in Silangit, the establishment of the Lake Toba Super Priority National Tourism Strategic Area (KSPN). The current Ministry of Tourism has made significant reforms, namely changing the focus from quantity tourism to quality tourism. The development of tourism quality that is currently underway in the Lake Toba area is then measured from the perceptions of tourists who respond to the quality values they have received while in the tourist area of Lake Toba. The theory used in this research is the theory of tourism by Nare, and the theory of foreign tourists by Ghanem. Furthermore, the method used is the quantitative data analysis method. Based on the results of the study it was found that the Cronbach's Alpha value was 0.931> 0.60, so as the basis for decision making in the reliability test, it can be concluded that the data tested was reliable or consistent and reliable. Tourism actors involved in the research were also mostly tourism actors in 2004, so based on their answers it was found that there was a significant change in perceptions of foreign tourists, namely 0.931%.

scholarly journals Modelling Decision Making under Uncertainty for Strategic Forecasting

2019 ◽  
Vol 8 (3) ◽  
pp. 7251-7255
Keyword(s):  
Decision Making ◽  
Economic Activity ◽  
Detrimental Effect ◽  
Decision Making Under Uncertainty ◽  
Decision Making Process ◽  
Insufficient Information ◽  
High Quality ◽  
Decision Making System ◽  
Specific Management ◽  
Selection Of

In current market conditions, the key to productive economic activity is the ability to provide a high-quality forecast, even in situations of insufficient information. Strategic forecasting refers to this type of activity, errors in which the actions of any company can have a detrimental effect on the fundamental level. The justification and selection of specific management decisions can often be carried out in conditions of uncertainty due to the inability to clearly predict the values of the final results of these decisions. The decision-making system within the framework of the strategic forecasting task should help maintain the effectiveness of actions by simplifying the picture of the real world by modelling it. While allowing to reduce the influence of the subjectivity of the personality of the decision-maker on the decision-making process itself

scholarly journals ACCOUNTING AND CONTROL OF INVENTORIES AS A BASIS FOR EFFECTIVE MANAGEMENT OF A TRADING ENTERPRISE

2020 ◽  
Author(s):  
Iryna Krupelnytska ◽  
Keyword(s):  
Decision Making ◽  
Quality Management ◽  
Management Accounting ◽  
Enterprise Management ◽  
Management Effectiveness ◽  
High Quality ◽  
Trading Company ◽  
And Control ◽  
Accounting Policy

Inventories are main resources of the trading company. Analysis, accounting and control of inventories determines the management effectiveness of commercial enterprises processes. It is necessary to accelerate the turnover of commodity resources in order to increase the profits of a trading company. Successful turnover of commodity resources can be determined with the help of high-quality operational management accounting information, which is the basis for analysis, decision-making and further control of the trading company. Obtaining management information achieved with establishment of an effective accounting policy, which is the direct responsibility of the company's management. The interdependence of the accounting policy type, quality management accounting, operational analysis and clear control over inventories at the trade enterprise determines the effectiveness of enterprise management and profit in the long-term perspective.

scholarly journals Advanced Deep Learning Model

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Deep Learning ◽  
Learning Algorithms ◽  
Learning Model ◽  
Intelligence Analysis ◽  
Basic Parameters ◽  
Deep Learning Model ◽  
Learning Sets

Deep learning is a type of machine learning that trains a computer to perform human-like tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing. This paper aims to illustrate some of the different deep learning algorithms and methods which can be applied to artificial intelligence analysis, as well as the opportunities provided by the application in various decision making domains.

A Recommender System Supporting Teachers to Author Learning Sessions in Decision-Making

2013 ◽  
pp. 1-29
Author(s):  
Arnoldo Rodríguez
Keyword(s):  
Decision Making ◽  
Automatic Generation ◽  
Teaching Materials ◽  
Web Based ◽  
Problem Of Time ◽  
Use Of Data ◽  
Network Topologies ◽  
Time To Learn ◽  
Time Required ◽  
Supporting Teachers

This chapter pays attention to the automatic generation and recommendation of teaching materials for teachers who do not have enough time to learn how to use authoring tools for the creation of materials to support their courses. To overcome the difficulties, the research is intended to solve the problem of time needed to create adapted case studies for teaching decision-making in network design. Another goal is to reduce the time required to learn the use of an authoring tool to create teaching materials. Thus, the author presents an assistant that provides adapted help for teachers, generates examples automatically, verifies that any generated example fits in the class of examples used by the teacher, and recommends personalized examples according to each teacher’s preferences. He studies the use of data related to teachers to support the recommendation of teaching materials and the adaptation of Web-based support. The automatic generation and test of examples of network topologies are based on a probabilistic model, and the recommendation is based on Bayesian classification. This investigation also looks at problems related to the application of Artificial Intelligence (AI) to support teachers in authoring learning sessions for Adaptive Educational Hypermedia (AEH).

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