Optimization of C.I Engine Parameters Using Artificial Neural

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...

Optimization of Antenna Parameters Using Artificial Neural Network: A Review

Microstrip Patch antenna is used in various antenna systems because of their low profile, light weight, low cost, compactness etc. Patch antenna is also used with Microwave IC’s and Monolithic Microwave IC’s because of its compatibility. Artificial neural network have become popular for predicting performance parameters of various antenna because of their learning and simplification features. T...

Prediction of Gas Lift Parameters Using Artificial Neural Networks

Artificial Neural Network Based Multi-Objective Evolutionary Optimization of a Heavy-Duty Diesel Engine

In this study the performance and emissions characteristics of a heavy-duty, direct injection, Compression ignition (CI) engine which is specialized in agriculture, have been investigated experimentally. For this aim, the influence of injection timing, load, engine speed on power, brake specific fuel consumption (BSFC), peak pressure (PP), nitrogen oxides (NOx), carbon dioxide (CO2), Carbon mon...

Artificial Neural Networks based Methodologies for Optimization of Engine Operations

This paper presents overview of applications of artificial neural networks (ANN) in the field of engine development. Various approaches using ANN are highlighted that resulted in better modeling of engine operations. Using ANN we can reduce engine development time. The paper discusses ANN approach, algorithms and importance of architecture. This will also help in advancing ANN research.