This work addresses an efficient neural network (NN) representation for the phase-field modeling of isotropic brittle fracture. In recent years, data-driven approaches, such as networks, have become active research field in mechanics. this contribution, deep networks—in particular, feed-forward (FFNN)—are utilized directly development failure model. The verification and generalization trained m...

Millions of people are dying, and billions properties damaged by road traffic accidents each year worldwide. In the case our country Ethiopia, effect is even more causing injuries, death, property damage. Forecasting accident predicting severity contributes a role indirectly in reducing accidents. This study deals with forecasting number prediction an Oromia Special Zone using deep artificial n...

Floods are one of the most common natural disasters that occur frequently causing massive damage to property, agriculture, economy and life. Flood prediction offers a huge challenge for researchers struggling predict floods since long time. In this article, flood forecasting model using federated learning technique has been proposed. Federated Learning is advanced machine (ML) guarantees data p...

Abstract The swelling of clay-sulfate rocks is a well-known phenomenon often causing threats to the success various geotechnical projects, including tunneling, road and bridge construction, geothermal drilling. origin usually explained by physical due clay expansion combined with chemical associated transformation anhydrite (CaSO 4 ) into gypsum ∙2H 2 O). latter occurs through dissolution subse...

In India, around 7 million people depend on fishing for their livelihoods. They are assisted with a reliable and fast brief forecast the areas of fish aggregations. Habitat mapping is critical in supporting strategic choices usage protection. conjunction techniques machine learning, remote control has made comprehensive relevant scales possible. supervised algorithms utilized to make forecasts ...

Abstract: This paper presents a dual neural network based technique for detecting and classifying the power quality disturbances. In the proposed method, Adaptive Linear Neural Network is used to extract the rms voltage for harmonics and Interharmonics estimations. With the help of these indices, PQ disturbances such as Sag, Swell, Outages are detected and classified, Harmonics and Interharmoni...

Automated grading system plays an important role in many industries. In ceramic industries, the grading of ceramic tiles is a difficult task as it has huge variations of surface properties. In this paper, automated surface grading system based on Discrete Wavelet Transform (DWT) and Gray Level Co-occurrence Matrices (GLCM) is presented. Texture information’s in ceramic tiles are effectively rep...