Diverse Applications of Neural Networks are driving their Demand in the Near Future

With technological advancements for data analysis, reducing cost and time across several enterprises, there has been a significant adoption of neural network software. Neural network software assist enterprises in business applications such as fraud detection or risk assessment. Neural network software are deployed across various streams viz. business analytics, product maintenance, financial operations, and trading.

Global Neural Network Software Market- Growth Driven by Rising Adoption of Data Achieving Tools

In its report, Future Market Insights delivers key analysis on the global neural network software market. The growth of the neural network software market is primarily attributed to increasing adoption of data achieving tools for organising excessive amount of unorganised data created by diverse end-users. In addition, growing utilisation of digital technologies, and increasing demand for predicting solutions are some other factors propelling the growth of market. In contrast, sluggish rate of digitisation across evolving regions, absence of technical expertise, and operational challenges are some factors expected to impede the growth of the global neural network software market in the near future.

Some Applications of Neural Networks Include

  • Advanced Melanoma Detection and Screening– An advanced image recognition was being put to work by researchers at University of Michigan, for detecting one of the most aggressive types of cancer, curable in early stages. Melanoma can’t only be deadly but is also difficult for screening accurately. The researchers trained one neural network for isolating features such as structure and texture of moles & suspicious lesions to better recognise them. According to the researchers, the experimental results obtained from quantitative and qualitative evaluations have demonstrated the outperformance of this method compared to other several state-of-art algorithms, for detection of melanoma.
  • Finance– A phenomenal success has been discerned by futures markets since their inception in both developing and developed economies over the past four decades. This success is primarily attributed to the provision of futures to market participants. A trading strategy benefits from the leverage by utilisation of cost-of-carry relationship, and Capital Asset Pricing Model (CAPM). Developed through spot market prices the technical trading rules were applied to futures market prices utilising CAPM-based hedge ratio. Daily historical costs of 20 stocks from ten markets were utilised for analysis by the researchers. Prevalent technical indicators, coupled with AI (artificial intelligence) techniques such as genetic algorithms and neural networks were utilised for generating selling and buying signals for every stock as well as for stock portfolios. Two particular areas for successful developments of neural networks are expected to be risk management and trading. Neural networks were also deployed for predicting corporate bankruptcies, and for determining large-scale financial & banking health.
  • Space Mission Efforts– A team of researchers from Italy had focused on CubeSats- a new space systems category for missions of low Earth orbit- facing various technical challenges on numerous fronts. These researchers were focused on attention on capabilities of event detection, coupled with an intention of enabling the autonomous operations for non-satellite missions through presentation of a neural network technology-based AI algorithm, applied to future mission utilised as case studies. This comprises a dense paper, particularly complex, with many unknowns, discerning considerations of neural networks for solving optimisation & other issues.
  • Event Detection and Weather Forecasting– Traditional area for the large-scale supercomputers has become a hotbed for development of neural networks, especially while considering weather even detection. In one such utilisation case, codes of computational fluid dynamics are matched with the neural networks & other genetic algorithm approaches for detecting cyclone activity.

The information presented here is sourced from Future Market Insights latest report. A sample of this report is available upon request.

Author: Abhishek Budholiya is a tech blogger, digital marketing pro, and has contributed to numerous tech magazines. Currently, as a technology and digital branding consultant, he offers his analysis on the tech market research landscape. His forte is analysing the commercial viability of a new breakthrough, a trait you can see in his writing. When he is not ruminating about the tech world, he can be found playing table tennis or hanging out with his friends.