Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy theory combining CPM computations, time-cost trade off analysis and resource constraint. MATLAB software has been adopted to perform ranking process, for each case, that
facilitates obtaining the optimum solution. This research infers that it is possible to perform time-cost trade off analysis with resource restriction simultaneously, which ensures achieving scheduling optimum solution reducing the effort and the time when performing these techniques in succession using traditional methods.
Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t
... Show MoreThe current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances. From the diversity of Big Data variables comes many challenges that can be interesting to the researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter
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Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model
In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe
... Show MoreThe problem of the study was to identify the possibility of benefiting from the application of the target cost system as a modern cost system to activate the environmental cost management instead of the traditional systems used in the company due to the great transformations witnessed by the business environment in all fields, which have resulted in the search for modern systems to provide more accurate and more appropriate information to reduce Costs, because accurate information makes the company have a complete vision to achieve the company’s goals. To solve this problem, the research was based on the following hypothesis (that the role of the target cost system leads to the activation of environmental cost management). Target c
... Show MoreIn this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method
In the present paper, discuss the concept of fuzzy topological spectrum of a bounded commutative KU-algebra and study some of the characteristics of this topology. Also, we show that the fuzzy topological spectrum of this structure is compact and T1 -space.
In this work the design and application of a fuzzy logic controller to DC-servomotor is investigated. The proposed strategy is intended to improve the performance of the original control system by use of a fuzzy logic controller (FLC) as the motor load changes. Computer simulation demonstrates that FLC is effective in position control of a DC-servomotor comparing with conventional one.
The purpose of this paper is to shed light on the concept of fuzzy logic ,its application in linguistics ,especially in language teaching and the fuzziness of some lexical items in English.
Fuzziness means that the semantic boundaries of some lexical items are indefinite and ideterminate.Fuzzy logic provides a very precise approach for dealing with this indeterminacy and uncertainty which grows (among other reasons) out of human behavior and the effect of society.
The concept of fuzzy logic has emerged in the development of the theory of fuzzy set by Lotfi Zadeh(a professor of computer science at the university of California) in 1965.It can be thought of as the application side of the fuzzy set theory. In linguistics, few scholars