Applying Fuzzy Logic of Expert Knowledge for Accurate Predictive Algorithms of Customer Traffic Flows in Theme Parks

2016 ◽  
Vol 15 (06) ◽  
pp. 1451-1468 ◽  
Author(s):  
Tomasz Korol ◽  
Anestis Fotiadis
Keyword(s):  
Fuzzy Logic ◽  
Expert Knowledge ◽  
Decision Rules ◽  
Theme Park ◽  
Traffic Flows ◽  
Theme Parks ◽  
Forecasting Models ◽  
Predictive Algorithms ◽  
The Individual ◽  
High Level

This study analyzes two forecasting models based on the application of fuzzy logic and evaluates their effectiveness in predicting visitor expenditure and length of stay at a popular theme park. The forecasting models are based on a set of more than 600 decision rules constructed in the form of a complex series of IF-THEN statements. These algorithms store expert knowledge. A descriptive instrument that records the individual visitor’s time spent and expenditure distribution on activities in the E-Da World in Taiwan was used to gather data. From a process of rigorous verification, the models developed are characterized by a high level of accuracy and efficiency.

scholarly journals MODELLING SUPPORT SYSTEMS FOR SELECTING PROFESSIONS FOR APPLICANTS IN THE CONTENT OF PERSONALIZATION OF EDUCATION

2020 ◽  
Vol 2 ◽  
pp. 83-97
Author(s):  
Huseyn Gasimov
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Initial Level ◽  
Knowledge And Skills ◽  
Individual Approach ◽  
Input Layer ◽  
Level Of Knowledge ◽  
The Individual ◽  
High Level ◽  
Education Process

Various methods are currently being used in examining the initial “START” knowledge of applicants and their placement for specialties. Studies show that applicants are placed on the decreasing principle in terms of their overall scores at universities. In this case, applicants with a high level of knowledge are placed in the prestigious specialties as medicine and law as they require high results. Though, while applying for other professions, the applicants do not perform enough results on the key disciplines for the profession, they are placed in those professions when the general results enable it. This causes them to face a number of problems while working both in education process and in the industry. To avoid this problem and to place applicants in a specialty that is more relevant to their level of knowledge, the introduction of an individual approach to the evaluation of initial level of knowledge may be more promising. This article presents a modeling of the "evaluation – placement" support system for the individual approach to assessing applicants' knowledge and positioning them in relevant specialties. The main goal of the system is to give each applicant the opportunity to choose and study the specialty that is more relevant to their knowledge and skills, as well as to analyze the results for each discipline along with the overall results. The system is implemented using fuzzy logic based artificial neural networks. The network consists of 100 neurons in the input layer, two hidden layers and one output layer. The number of neurons at the output is the same as the number of specialties taught at university.

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Raid Daoud ◽  
Yaareb Al-Khashab
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Input Parameter ◽  
Traffic Density ◽  
The Internet ◽  
Linguistic Variables ◽  
Internet Service ◽  
Traffic Distribution ◽  
Smart Control ◽  
High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

Territorial Distribution of Alcohol and Drug Addictions Mortality Concerning Regional Disparities in the Slovak Republic from Year 1996 to Year 2015

2020 ◽  
Keyword(s):  
Mortality Rate ◽  
Slovak Republic ◽  
Regional Disparities ◽  
Point Of View ◽  
Extreme Position ◽  
Data Set ◽  
Female Sex ◽  
Male Sex ◽  
The Individual ◽  
High Level

BACKGROUND: This paper deals with territorial distribution of the alcohol and drug addictions mortality at a level of the districts of the Slovak Republic. AIM: The aim of the paper is to explore the relations within the administrative territorial division of the Slovak Republic, that is, between the individual districts and hence, to reveal possibly hidden relation in alcohol and drug mortality. METHODS: The analysis is divided and executed into the two fragments – one belongs to the female sex, the other one belongs to the male sex. The standardised mortality rate is computed according to a sequence of the mathematical relations. The Euclidean distance is employed to compute the similarity within each pair of a whole data set. The cluster analysis examines is performed. The clusters are created by means of the mutual distances of the districts. The data is collected from the database of the Statistical Office of the Slovak Republic for all the districts of the Slovak Republic. The covered time span begins in the year 1996 and ends in the year 2015. RESULTS: The most substantial point is that the Slovak Republic possesses the regional disparities in a field of mortality expressed by the standardised mortality rate computed particularly for the diagnoses assigned to the alcohol and drug addictions at a considerably high level. However, the female sex and the male sex have the different outcome. The Bratislava III District keeps absolutely the most extreme position. It forms an own cluster for the both sexes too. The Topoľčany District bears a similar extreme position from a point of view of the male sex. All the Bratislava districts keep their mutual notable dissimilarity. Contrariwise, evaluation of a development of the regional disparities among the districts looks like notably heterogeneously. CONCLUSIONS: There are considerable regional discrepancies throughout the districts of the Slovak Republic. Hence, it is necessary to create a common platform how to proceed with the solution of this issue.

Quantitative indicators of air traffic controllers’ attitude to the danger of errors

2020 ◽  
pp. 68-78
Author(s):  
O. M. Reva ◽  
V. V. Kamyshin ◽  
S. P. Borsuk ◽  
V. A. Shulhin ◽  
A. V. Nevynitsyn
Keyword(s):  
Human Factor ◽  
Differential Method ◽  
Air Traffic ◽  
Professional Activity ◽  
Aviation Accidents ◽  
Air Traffic Controllers ◽  
The Difference ◽  
Level Of Significance ◽  
The Individual ◽  
High Level

The negative and persistent impact of the human factor on the statistics of aviation accidents and serious incidents makes proactive studies of the attitude of “front line” aviation operators (air traffic controllers, flight crewmembers) to dangerous actions or professional conditions as a key component of the current paradigm of ICAO safety concept. This “attitude” is determined through the indicators of the influence of the human factor on decision-making, which also include the systems of preferences of air traffic controllers on the indicators and characteristics of professional activity, illustrating both the individual perception of potential risks and dangers, and the peculiarities of generalized group thinking that have developed in a particular society. Preference systems are an ordered (ranked) series of n = 21 errors: from the most dangerous to the least dangerous and characterize only the danger preference of one error over another. The degree of this preference is determined only by the difference in the ranks of the errors and does not answer the question of how much time one error is more dangerous in relation to another. The differential method for identifying the comparative danger of errors, as well as the multistep technology for identifying and filtering out marginal opinions were applied. From the initial sample of m = 37 professional air traffic controllers, two subgroups mB=20 and mG=7 people were identified with statisti-cally significant at a high level of significance within the group consistency of opinions a = 1%. Nonpara-metric optimization of the corresponding group preference systems resulted in Kemeny’s medians, in which the related (middle) ranks were missing. Based on these medians, weighted coefficients of error hazards were determined by the mathematical prioritization method. It is substantiated that with the ac-cepted accuracy of calculations, the results obtained at the second iteration of this method are more ac-ceptable. The values of the error hazard coefficients, together with their ranks established in the preference systems, allow a more complete quantitative and qualitative analysis of the attitude of both individual air traffic controllers and their professional groups to hazardous actions or conditions.

scholarly journals Automatic Labeled Dialogue Generation for Nursing Record Systems

2020 ◽  
Vol 10 (3) ◽  
pp. 62
Author(s):  
Tittaya Mairittha ◽  
Nattaya Mairittha ◽  
Sozo Inoue
Keyword(s):  
Data Augmentation ◽  
Short Term Memory ◽  
Generative Models ◽  
Abstract Knowledge ◽  
Augmentation Techniques ◽  
Nursing Record ◽  
Long Short Term Memory ◽  
The Individual ◽  
High Level ◽  
Embedding Methods

The integration of digital voice assistants in nursing residences is becoming increasingly important to facilitate nursing productivity with documentation. A key idea behind this system is training natural language understanding (NLU) modules that enable the machine to classify the purpose of the user utterance (intent) and extract pieces of valuable information present in the utterance (entity). One of the main obstacles when creating robust NLU is the lack of sufficient labeled data, which generally relies on human labeling. This process is cost-intensive and time-consuming, particularly in the high-level nursing care domain, which requires abstract knowledge. In this paper, we propose an automatic dialogue labeling framework of NLU tasks, specifically for nursing record systems. First, we apply data augmentation techniques to create a collection of variant sample utterances. The individual evaluation result strongly shows a stratification rate, with regard to both fluency and accuracy in utterances. We also investigate the possibility of applying deep generative models for our augmented dataset. The preliminary character-based model based on long short-term memory (LSTM) obtains an accuracy of 90% and generates various reasonable texts with BLEU scores of 0.76. Secondly, we introduce an idea for intent and entity labeling by using feature embeddings and semantic similarity-based clustering. We also empirically evaluate different embedding methods for learning good representations that are most suitable to use with our data and clustering tasks. Experimental results show that fastText embeddings produce strong performances both for intent labeling and on entity labeling, which achieves an accuracy level of 0.79 and 0.78 f1-scores and 0.67 and 0.61 silhouette scores, respectively.

scholarly journals Opportunities and Challenges of Green-Lean: An Integrated System for Sustainable Construction

2020 ◽  
Vol 12 (11) ◽  
pp. 4460 ◽  
Author(s):  
Mohammadsoroush Tafazzoli ◽  
Ehsan Mousavi ◽  
Sharareh Kermanshachi
Keyword(s):  
Cost Savings ◽  
Integrated Approach ◽  
Integrated System ◽  
Waste Minimization ◽  
Sustainable Construction ◽  
Future Research ◽  
Safety Improvement ◽  
The Individual ◽  
High Level ◽  
Industry Professionals

Although the two concepts of lean and sustainable construction have been developed due to different incentives, and they do not pursue the same exact goals, there exists considerable commonality between them. This paper discusses the potentials for integrating the two approaches and their practices and how the resulting synergy from combining the two methods can potentially lead to higher levels of fulfilling the individual goals of each of them. Some limitations and challenges to implementing the integrated approach are also discussed. Based on a comprehensive review of existing papers related to sustainable and lean construction topics, the commonality between the two approaches is discussed and grouped in five categories of (1) cost savings, (2) waste minimization, (3) Jobsite safety improvement, (4) reduced energy consumption, and (5) customers’ satisfaction improvement. The challenges of this integration are similarly identified and discussed in the four main categories of (1) additional initial costs to the project, (2) difficulty of providing specialized expertise, (3) contractors’ unwillingness to adopt the additional requirements, and (4) challenges to establish a high level of teamwork. Industry professionals were then interviewed to rank the elements in each of the two categories of opportunities and challenges. The results of the study highlight how future research can pursue the development of a new Green-Lean approach by investing in the communalities and meeting the challenges of this integration.

scholarly journals Fuzzy Logic for Intelligent Control System Using Soft Computing Applications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2617
Author(s):  
Catalin Dumitrescu ◽  
Petrica Ciotirnae ◽  
Constantin Vizitiu
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Control Technique ◽  
Distributed Intelligence ◽  
High Level ◽  
The Impact ◽  
Fuzzy Subsets

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.

scholarly journals Children’s Astronomy. Development of the Shape of the Earth Concept in Polish Children between 5 and 10 Years of Age

2021 ◽  
Vol 11 (2) ◽  
pp. 75
Author(s):  
Jan Amos Jelinek
Keyword(s):  
Mental Model ◽  
Cultural Influences ◽  
Test Results ◽  
The Earth ◽  
Spherical Earth ◽  
The Individual ◽  
High Level ◽  
Cognitive Problems ◽  
Teaching Situations ◽  
Model Approach

The Earth’s shape concept develops as consecutive cognitive problems (e.g., the location of people and trees on the spherical Earth) are gradually resolved. Establishing the order of problem solving may be important for the organisation of teaching situations. This study attempted to determine the sequence of problems to be resolved based on tasks included in the EARTH2 test. The study covered a group of 444 children between 5 and 10 years of age. It captured the order in which children solve cognitive problems on the way to constructing a science-like concept. The test results were compared with previous studies. The importance of cultural influences connected to significant differences (24%) in test results was emphasised. Attention was drawn to the problem of the consistency of the mental model approach highlighted in the literature. The analysis of the individual sets of answers provided a high level of consistency of indications referring to the same model (36%), emphasising the importance of the concept of mental models.

scholarly journals Experts versus Algorithms? Optimized Fuzzy Logic Energy Management of Autonomous PV Hybrid Systems with Battery and H2 Storage

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1777
Author(s):  
Lisa Gerlach ◽  
Thilo Bocklisch
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Fuzzy Logic Controller ◽  
Expert Knowledge ◽  
Large Power ◽  
Hybrid Energy ◽  
Knowledge Based ◽  
Long Term Storage ◽  
Fuzzy Logic Approach

Off-grid applications based on intermittent solar power benefit greatly from hybrid energy storage systems consisting of a battery short-term and a hydrogen long-term storage path. An intelligent energy management is required to balance short-, intermediate- and long-term fluctuations in electricity demand and supply, while maximizing system efficiency and minimizing component stress. An energy management was developed that combines the benefits of an expert-knowledge based fuzzy logic approach with a metaheuristic particle swarm optimization. Unlike in most existing work, interpretability of the optimized fuzzy logic controller is maintained, allowing the expert to evaluate and adjust it if deemed necessary. The energy management was tested with 65 1-year household load datasets. It was shown that the expert tuned controller is more robust to changes in load pattern then the optimized controller. However, simple readjustments restore robustness, while largely retaining the benefits achieved through optimization. Nevertheless, it was demonstrated that there is no one-size-fits-all tuning. Especially, large power peaks on the demand-side require overly conservative tunings. This is not desirable in situations where such peaks can be avoided through other means.

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