The basic element of a project organizing construction works is a schedule. The preparation of the data necessary to specify the timings of the construction completion as indicated in the schedule involves information that is uncertain and hard to quantify. The article presents the methods of building a schedule which includes a fuzzy amount of labour, time standards and number of workers. The proposed procedure allows determining the real deadline for project completion, taking into account variable factors affecting the duration of the individual works.

During implementation of construction projects, durations of activities are affected by various factors. Because of this, both during the planning phase of the project as well as the construction phase, managers try to estimate, or predict, the length of any delays that may occur. Such estimates allow for the ability to take appropriate action in terms of planning and management during the execution of construction works. This paper presents the use of the non-deterministic concept for describing the uncertainty of estimating works duration. The concept uses the theory of fuzzy sets. The author describes a method for fuzzy estimations of construction works duration based on the fact that uncertain data is an inherent factor in the conditions of construction projects. An example application of the method is presented. The author shows a fuzzy estimation for the duration of an activity, taking into consideration the distorting influence caused by malfunctioning construction equipment and delivery delays of construction materials.

The paper shows methods of analysis and assessment of partnering relations of construction enterprises with the use of questionnaires, statistics, and fuzzy logic. The results were obtained from Polish, Slovak and Ukrainian enterprises. The definition of partnering in the construction industry indicates that it is a qualitative concept. By applying a scale in the questionnaire, and due to mathematical analysis of the data, the final research result, showing the level of partnering relations of construction enterprises, is rendered quantitatively.

The protection of Polish architectural heritage in the former eastern borderlands, accomplished through the conservation and technical securing of historical structures, constitutes one of the main programmes that are implemented by the Ministry of Culture and National Heritage. Currently, many Polish historical buildings in the former eastern borderlands are in a very bad technical condition. The load-bearing systems of these elements, as well as elements of their finish, require immediate emergency securing work. The basic steps that precede conservation work are emergency structural works, which guarantee the durability and stability of the entire historical substance. The specifics and complexity of the problem of the failure of historical buildings often demands an in-depth analysis of a series of factors that are difficult to measure and which are responsible for the cause and effect relationship during the early stage of the technical evaluation of a structure. The analyses of failures of numerous historical structures, for instance that were carried out by the authors, have become the inspiration for the search for effective methods of analysis that would allow for an in-depth analysis of the causes and effects of the failures in question. The DEMATEL method (Decision Making Trial and Evaluation Laboratory) that has been presented in this work, and its fuzzy extension, has lately become one of the more popular methods used in the cause-and-effect analysis of various phenomena. The authors demonstrated how this method works on the example of the evaluation and securing of the load-bearing system of the XVII Collegiate church of the Holy Trinity in the town of Olykha in the Volhynskiy Oblast, Ukraine.

The article introduces a new proposal of a defuzzification method, which can be implemented in fuzzy controllers. The first chapter refers to the origin of fuzzy sets. Next, a modern development based on this theory is presented in the form of ordered fuzzy numbers (OFN). The most important characteristics of ordered fuzzy numbers are also presented. In the following chapter, details about the defuzzification process are given as part of the fuzzy controller model. Then a new method of defuzzification is presented. The method is named center of circles intersection (CCI). The authors compare this method with a similar geometric solution: triangular expanding (TE) and geometric mean (GM). Also, the results are compared with other methods such as center of gravity (COG), first of maxima (FOM) and last of maxima (LOM). The analysis shows that the proposed solution works correctly and provides results for traditional fuzzy numbers as well as directed fuzzy numbers. The last chapter contains a summary, in which more detailed conclusions are provided and further directions of research are indicated.

In the paper issues related to the design of a robust adaptive fuzzy estimator for a drive system with a flexible joint is presented. The proposed estimator ensures variable Kalman gain (based on the Mahalanobis distance) as well as the estimation of the system parameters (based on the fuzzy system). The obtained value of the time constant of the load machine is used to change the values in the system state matrix and to retune the parameters of the state controller. The proposed control structure (fuzzy Kalman filter and adaptive state controller) is investigated in simulation and experimental tests.

The idea of using the Cloud of Things is becoming more critical for e-government, as it is considered to be a useful mechanism of facilitating the government’s work. The most important benefit of using the Cloud of Things concept is the increased productivity that the e-governments would achieve; which eventually would lead to significant cost savings; which in turn would have a highly anticipated future impact on egovernments. E-government’s diversity goals face many challenges; trust is one of the major challenges that it is facing when deploying the Cloud of Things. In this study, a new trust framework is proposed which supports trust with the Internet of Things devices interconnected to the cloud; to support the services that are provided by e-government to be delivered in a trusted manner. The proposed framework has been applied to a use case study to ensure its trustworthiness in a real mission. The results show that the proposed trust framework is useful to ensure achieving a trusted environment for the Cloud of Things for it to continue providing and gathering the data needed for the services that are offered by users through E-government.

Fuzzy logic determination of the material hardening parameters based on the Heyer’s method was applied in this research. As the fuzzy input variables, the length of two measuring bases and the maximum force registered in the Heyer’s test were used. Firstly, the numerical experiment (the simulation of the fuzzification of the input data) with the assumed disturbance of input variables was performed. Next, on the basis of experimental investigations (eleven samples made from the same material), the membership functions associated with the input data were created. After that, the fuzzy analysis was examined. Fuzzy material hardening constants obtained by means of the α-level optimization and the extension principle methods were compared. Discrete values of the hardening data are found in the defuzzification process, by application of the mass center method.

The computational intelligence tool has major contribution to analyse the properties of materials without much experimentation. The B4C particles are used to improve the quality of the strength of materials. With respect to the percentage of these particles used in the micro and nano, composites may fix the mechanical properties. The different combinations of input parameters determine the characteristics of raw materials. The load, content of B4C particles with 0%, 2%, 4%, 6%, 8% and 10% will determine the wear behaviour like CoF, wear rate etc. The properties of materials like stress, strain, % of elongation and impact energy are studied. The temperature based CoF and wear rate is analysed. The temperature may vary between 30°C, 100°C and 200°C. In addition, the CoF and wear rate of materials are predicted with respect to load, weight % of B4C and nano hexagonal boron nitride %. The intelligent tools like Neural Networks (BPNN, RBNN, FL and Decision tree) are applied to analyse these characteristics of micro / nano composites with the inclusion of B4C particles and nano hBN % without physically conducting the experiments in the Lab. The material properties will be classified with respect to the range of input parameters using the computational model.

Currently commercialization of electric vehicle (EV) is based to minimize the time of starting and acceleration. To undergo this problem multi-input multi-output fuzzy logic controller (MIMO-FLC) affect on propelled traction system forming MMS process was proposed. This paper introduces a MIMO-FLC applied on speeds of electric vehicle, the electric drive consists of two directing wheels and two rear propulsion wheels equipped with two light weight induction motors. The EV is powered by two motors of 37 kilowatts each one, delivering a 476 Nm total torque. Its high torque (476Nm) is instantly available to ensure responsive acceleration performance in built-up areas. Acceleration and steering are ensured by an electronic differential system which maintains robust control for all cases of vehicle behavior on the road. It also allows controlling independently every driving wheel to turn at different speeds in any curve. Direct torque control based on space vector modulation (DTC-SVM) is proposed to achieve the tow rear driving wheel control. The MIMO-FLC control technique is simulated in MATLAB SIMULINK environment. The simulation results have proved that the MIMO-FLC method decreases the transient oscillations and assure efficiency comportment in all type of road constraints, straight, slope, descent and curved road compared to the single input single output fuzzy controller (SISO-FLC).

Hydrocarbon production under certain geological conditions of these deposits can cause surface subsidence and deformation of the terrain surface. Such deformations appear as subsidence troughs of considerable range and the magnitude of the subsidence depending on the total thickness of the reservoir, compaction properties of reservoir and on the number of other factors. In the past there have been widely recognized magnitudes of the subsidence up to 9 meters. The stress zones in the subsidence trough may affect the buildings and surface structures. However there have been well known some cases of destroyed boreholes or pipelines belonging to the gas or oil mine. Therefore there is a requirement to analyze the possibility of occurrence unfavorable phenomenon on the ground surface, to monitor surface deformations during production and to protect surface infrastructure located in the range of mining influences. In the paper the issue of surface subsidence caused by hydrocarbon production has been presented. The cause - effect relationship between the compaction of thereservoir rock and the subsidence of surface area has been assumed. The prediction model base on the influence function and on the superposition of elementary influences. For the purpose of building damage protection a new model of risk assessment has been developed. This model base on the elements of fuzzy logicallows to incorporate in the analysis the quantitative and qualitative factors that contribute to the risk of building damage. Use of the fuzzy logic made it possible to obtain one value which clearly discriminate the risk of buildings damage. However, risk analyzes of damage to the large number of buildings has been required additional tools. The spatial analysis has been made by using GIS. The subjects of the paper have been illustrated with a practical example.

The information technologies for assessing the quality of IT-specialties graduates' training of university by means of fuzzy logic and neural networks are developed in the article. It makes possible taking into account a wide set of estimation and output parameters, influence of the external and internal factors and allows to simplify the assessing process by means of modern mathematical apparatuses of artificial intelligence.

The interrelation between fuzzy logic and cluster renewal approaches for heat transfer modeling in a circulating fluidized bed (CFB) has been established based on a local furnace data. The furnace data have been measured in a 1296 t/h CFB boiler with low level of flue gas recirculation. In the present study, the bed temperature and suspension density were treated as experimental variables along the furnace height. The measured bed temperature and suspension density were varied in the range of 1131–1156 K and 1.93–6.32 kg/m3, respectively. Using the heat transfer coefficient for commercial CFB combustor, two empirical heat transfer correlation were developed in terms of important operating parameters including bed temperature and also suspension density. The fuzzy logic results were found to be in good agreement with the corresponding experimental heat transfer data obtained based on cluster renewal approach. The predicted bed-to-wall heat transfer coefficient covered a range of 109–241 W/(m2K) and 111–240 W/(m2), for fuzzy logic and cluster renewal approach respectively. The divergence in calculated heat flux recovery along the furnace height between fuzzy logic and cluster renewal approach did not exceeded ±2%.

Solar energy is widely available in nature and electricity can be easily extracted using solar PV cells. A fuel cell being reliable and environment friendly becomes a good choice for the backup so as to compensate for continuously varying solar irradiation. This paper presents simple control schemes for power management of the DC microgrid consisting of PV modules and fuel cell as energy sources and a hydrogen electrolyzer system for storing the excess power generated. The supercapacitor bank is used as a short term energy storage device for providing the energy buffer whenever sudden fluctuations occur in the input power and the load demand. A new power control strategy is developed for a hydrogen storage system. The performance of the system is assessed with and without the supercapacitor bank and the results are compared. A comparative study of the voltage regulation of the microgrid is presented with the controller of the supercapacitor bank, realized using a traditional PI controller and an intelligent fuzzy logic controller.

The quality of the squeeze castings is significantly affected by secondary dendrite arm spacing, which is influenced by squeeze cast input

parameters. The relationships of secondary dendrite arm spacing with the input parameters, namely time delay, pressure duration, squeeze

pressure, pouring and die temperatures are complex in nature. The present research work focuses on the development of input-output

relationships using fuzzy logic approach. In fuzzy logic approach, squeeze cast process variables are expressed as a function of input

parameters and secondary dendrite arm spacing is expressed as an output parameter. It is important to note that two fuzzy logic based

approaches have been developed for the said problem. The first approach deals with the manually constructed mamdani based fuzzy

system and the second approach deals with automatic evolution of the Takagi and Sugeno’s fuzzy system. It is important to note that the

performance of the developed models is tested for both linear and non-linear type membership functions. In addition the developed models

were compared with the ten test cases which are different from those of training data. The developed fuzzy systems eliminates the need of

a number of trials in selection of most influential squeeze cast process parameters. This will reduce time and cost of trial experimentations.

The results showed that, all the developed models can be effectively used for making prediction. Further, the present research work will

help foundrymen to select parameters in squeeze casting to obtain the desired quality casting without much of time and resource

consuming.

This paper presents methods for optimal test frequencies search with the use of heuristic approaches. It includes a short summary of the analogue circuits fault diagnosis and brief introductions to the soft computing techniques like evolutionary computation and the fuzzy set theory. The reduction of both, test time and signal complexity are the main goals of developed methods. At the before test stage, a heuristic engine is applied for the principal frequency search. The methods produce a frequency set which can be used in the SBT diagnosis procedure. At the after test stage, only a few frequencies can be assembled instead of full amplitude response characteristic. There are ambiguity sets provided to avoid a fault tolerance masking effect.

The article includes presentation of fuzzy numbers application in projects prioritizing at

manufacturing and service providing enterprises. The following criteria have been applied

as a basis for projects prioritizing analysis in enterprise: NPV index, linked with the enterprise strategic aims, project execution cost, project time, project scope and risk. As the

criteria selected were of measurable and non-measurable character in projects prioritizing

evaluation, the fuzzy decision making system has been developed, in which a linguistic value

has been defined for each criterion of projects prioritizing. Knowledge base has been developed afterwards, presenting cause-effect dependencies in projects prioritizing. Knowledge

base consisted of conditional rules. Fuzzy system of decision making in project prioritizing

has been developed in MATLAB application.

The decision making fuzzy system established, constitutes an efficient tool for projects prioritizing, on the basis of criteria given and concluding system developed. The obtained analysis

results provide basis for the decision making parties to set the projects execution sequences.