In this research was to use the method of classic dynamic programming (CDP) and the method of fuzzy dynamic programming (FDP) to controlling the inventory in N periods and only one substance ,in order to minimize the total cost and determining the required quantity in warehouse rusafa principal of the ministry of commerce . A comparison was made between the two techniques، We found that the value of fuzzy total cost is less than that the value of classic total cost

The best proximity point is a generalization of a fixed point that is beneficial when the contraction map is not a self-map. On other hand, best approximation theorems offer an approximate solution to the fixed point equation . It is used to solve the problem in order to come up with a good approximation. This paper's main purpose is to introduce new types of proximal contraction for nonself mappings in fuzzy normed space and then proved the best proximity point theorem for these mappings. At first, the definition of fuzzy normed space is given. Then the notions of the best proximity point and - proximal admissible in the context of fuzzy normed space are presented. The notion of α ̃–ψ ̃- proximal contractive mapping is introduced.

This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

The pillars of sustainable development are representing the interface between environmental, economic, and social sustainability. Sustainable development is a method of planning and managing construction projects to reduce the effect of the construction process on the environment so that there is a balance between environmental capabilities and the human needs of present and future generations. Usually, Environmental sustainability is most important and effective in construction projects. The environment suffers from significant negative impacts as a result of the implementation of construction projects; therefore, this study aims to identify the effecting factors on environmentally sustainable development. The methodology of this s

We demonstrate that the selective hydrogenation of acetylene depends on energy profile of the partial and full hydrogenation routes and the thermodynamic stability of adsorbed C₂H₂ in comparison to C₂H₄.