Generalised single valued neutrosophic number and its application to neutrosophic linear programming

In this paper, the concept of single valued neutrosophic number (SV N-number) is presented in a generalized way. Using this notion, a crisp linear programming problem (LP-problem) is extended to a neutrosophic linear programming problem (NLP-problem). The coefficients of the objective function of a crisp LP-problem are considered as generalized single valued neutrosophic number (GSV N -number). This modified form of LP-problem is here called an NLP-problem. An algorithm is developed to solve NLP-problem by simplex method. Finally, this simplex algorithm is applied to a real life problem. The problem is illustrated and solved numerically

AN INNOVATIVE APPROACH OF INTUIONISTIC FUZZY NUMBERS IN CALCULATION OF STRESS AND DEFLECTION OF A COMPOSITE BAR

In the analysis and design of structures, an important aspect is the deformationcaused by the loads applied at them. Analyzing the deformations helps in calculating thestress in the structures. Usually the distribution of stress cannot be clearly determined alongthe structure as it is uncertain. This paper proposes an innovative method to find the stress anddeflection of a composite bar using Horizontal relative trapezoidal intuitionistic fuzzy number(HRTrIFN) as Young’s modulus values. The bending point at any location along the beamcan be calculated since the stress and deflection values are found as range of values, the actualbending point, peak and the breaking point of the beam can be calculated efficiently which isfar more better than the traditional method where it is a single crisp value. This helps theanalyst to determine very accurately the strength of the structure

Earliest Diabetic Retinopathy Classification Using Deep Convolution Neural Networks.pdf

<div>Expanding need about finding a diabetic retinopathy Similarly as soonest might stop dream misfortune to the prolonged</div><div>diabetes tolerant In spite of endured youngs. Seriousness of the diabetic retinopathy illness may be measured In light of</div><div>microaneurysms, exudates detections and it evaluations Similarly as Non-proliferative(NPDR) alternately Proliferative</div><div>diabetic retinopathy patient(PDR). An recommended machine Taking in approach for example, a Convolutional neural</div><div>Network(CNN) provides for helter skelter correctness over characteristic identification. "around different regulated and</div><div>unsupervised Taking in calculations involved, those suggested result is with find An preferred Furthermore optimized path</div><div>should identifying microaneurysms, exudates alternately seeped blood vessels. CNN may be flexible, deep, biologicallyinspired</div><div>variants for multi-layer perceptrons that bring turned out remarkable On picture characterizations. An profound</div><div>cascaded layers yield around 93-94% exactness Also outperforms other existing managed calculations. A profound</div><div>convolutional neural system layers need aid tried with those fundus picture database for example, such that DIARETDB0</div><div>need aid accessible publicly.</div