scholarly journals A Journal on Cervical Cancer Prediction Using Artificial Neural Networks

2021 ◽  
Vol 12 (2) ◽  
pp. 1085-1091
Author(s):  
K.Deepa , Et. al.
Keyword(s):  
Neural Networks ◽  
Cervical Cancer ◽  
Artificial Neural Networks ◽  
Death Rate ◽  
Developed Countries ◽  
Medical Procedures ◽  
Clinical Imaging ◽  
Cancer Prediction ◽  
Artificial Neural ◽  
Cervical Cells

Artificial neural networks (ANN) assume a significant part in numerous clinical imaging applications. Cervical cancer ranks the 4th dangerous women cancers in less developed countries due to insufficient trained staffs and medical procedures. The location of cervical malignancy cells utilizes ANN for characterizing the typical and unusual cells in the cervix wall of the uterus. Cervical malignancy location is exceptionally difficult on the grounds that this disease happens with no manifestations.  The order between the typical,unusual and malignant cells produces exact outcomes than other manual screening techniques.The ANN utilizes a few models for a simple and precise identification of cervical cells. The main aim of artificial neural networks is to supply right information at a right time. Hence we implement artificial neural techniques with collected data Analysis,to improve the life of an individual and to decrease the death rate of the society respectively.   

scholarly journals Artificial Neural Networks in Pavement Engineering: A Recent Review

2021 ◽  
Author(s):  
Abhishek Kurian ◽  
Elvin Sunildutt
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Deep Learning ◽  
Civil Engineering ◽  
Developed Countries ◽  
Pavement Management ◽  
Economic Management ◽  
Learning Techniques ◽  
Pavement Engineering ◽  
Artificial Neural

The application of Artificial Neural Networks (ANN) in civil engineering has increased drastically in the past few years. ANN tools are nowadays used commonly in developed countries over various fields of civil engineering like geotechnical, structural, traffic, pavement engineering etc. This paper deals with the review of recent advancements and utilization of ANNs in pavement engineering. The review will focus on pavement performance prediction, maintenance strategies, distress intensity detection through deep learning techniques, pavement condition index prediction etc. The use of ANNs in pavement management systems are expected to furnish a systematic schedule and economic management strategies in the field of pavement engineering. The use of ANNs combined with deep learning techniques help to address complex problems in pavement engineering and pave the way to a sustainable future.

scholarly journals Using an Artificial Neural Networks Experiment to Assess the Links among Financial Development and Growth in Agriculture

2021 ◽  
Vol 13 (5) ◽  
pp. 2828
Author(s):  
Cosimo Magazzino ◽  
Marco Mele ◽  
Fabio Gaetano Santeramo
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Financial Development ◽  
Agricultural Sector ◽  
Developed Countries ◽  
Large Set ◽  
Credit Access ◽  
Developed Economies ◽  
Specific Effects ◽  
Artificial Neural

Financial development, productivity, and growth are interconnected, but the direction of causality remains unclear. The relevance of these linkages is likely different for developing and developed economies, yet comparative cross-country studies are scant. The paper analyses the relationship among credit access, output and productivity in the agricultural sector for a large set of countries, over the period 2000–2012, using an Artificial Neural Networks approach. Empirical findings show that these three variables influence each other reciprocally, although marked differences exist among groups of countries. The role of credit access is more prominent for the OECD countries and less important for countries with a lower level of economic de-elopement. Our analysis allows us to highlight the specific effects of credit in stimulating the development of the agricultural sector: in developing countries, credit access significantly affects production, whereas in developed countries, it also has an impact on productivity.

scholarly journals Conditions Of Polish Industry Innovativeness

2011 ◽  
Vol 1 (3) ◽  
Author(s):  
Adam Mazurkiewicz ◽  
Rozalia Sitkowska ◽  
Magdalena Trzos
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Developed Countries ◽  
Development Activity ◽  
Intensity Index ◽  
Artificial Neural ◽  
Polish Economy ◽  
High Level ◽  
Innovation Intensity ◽  
The Eu

One of the measures of Polish economy development, including its innovativeness and competitiveness is the level of gross domestic expenditures on research and development activity, so called GERD in relation to gross domestic product, i.e. GDP. Poland assigns for R&D one tenth of expenditures, which are assigned by countries with the highest index GERD/GDP: USA and Japan. Scientific and research-development units in our country are characterised by a relatively low level of investment expenditures. As a result, small rebuild scientific-research apparatus and high level of its wear occur. The level of expenditures on R&D per capita in Poland and small share of industry in financing research are reasons of still unsatisfactory pace of decreasing the distance between Poland and well - developed countries (including the EU countries). Lack of mechanisms encouraging industry to greater participation in expenditures on R&D destimulates innovativeness and competitiveness of economy. The paper presents indexes characterising the innovative potential of Polish economy against the background of selected countries. It analyses positive aspects and barriers of innovativeness growth. These problems make a subject of many years research and analyses carried out by authors presented among others in works [1], [2]. The paper described some trends and conditions occurring in Polish economy undergoing transformation. It presents an example of using a method of artificial neural networks in modelling innovativeness in industry on an example of the innovation intensity index. Research method proposed by authors, carried out with the use of a method of artificial neural networks confirm that positive trends concerning Polish industry innovativeness in the first years of the XXI century are maintained.

scholarly journals Prediction prices of basrah light oil using artificial neural networks

2020 ◽  
Vol 10 (3) ◽  
pp. 2682
Author(s):  
Maysaa Abd Ulkareem Naser
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Economic Activity ◽  
Global Economy ◽  
Time Series Data ◽  
Supply And Demand ◽  
Oil Prices ◽  
Developed Countries ◽  
Series Data ◽  
Artificial Neural

The global economy is assured to be very sensitive to the volatility of the oil market. The beneficial from oil prices collapse are both consumers and developed countries. Iraq economy is a one-sided economy which is completely depends on oil revenue to charge the economic activity. Hence, the current decline in oil prices will produce serious concerns. Some factors stopped most investment projects, rationalize the recurrent outflow, and decrease the development of economic activity. The study of forecast oil prices is considered among the most complex studies because of the different dynamic variables that affects the strategic goods. Moreover, the laws of economics controlling the prices of oil such as the supply and demand law. Some other variables that control the oil prices are the political conditions when these conditions contribute to the world production. The subject of forecasting has been extremely developing during recent years and some modern methods have been appeared in this regards, for example, Artificial Neural Networks. In this study, an artificial neural network (FFNN) is adopted to extract the complex relationships among divergent parameters that have the abilities to predict oil prices serving as an inputs to the network data collected in this research represent monthly time series data are Oil prices series in (US dollars) over a period of 11 years (2008–2018) in Iraq

scholarly journals Classification of Cervical Cancer Using Artificial Neural Networks

2016 ◽  
Vol 89 ◽  
pp. 465-472 ◽  
Author(s):  
M. Anousouya Devi ◽  
S. Ravi ◽  
J. Vaishnavi ◽  
S. Punitha
Keyword(s):  
Neural Networks ◽  
Cervical Cancer ◽  
Artificial Neural Networks ◽  
Artificial Neural
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