Design Analysis and Implementation of Stock Market Forecasting System using Improved Soft Computing Technique

In this paper, a stock market prediction model was created utilizing artificial neural networks. Many people nowadays are attempting to predict future trends in bonds, currencies, equities, and stock markets. It is quite challenging for a capitalist and an industry to forecast changes in stock market prices. Due to the numerous economic, political, and psychological aspects at play, forecasting future value changes on the stock markets is quite challenging. In addition, stock market forecasting is a difficult endeavor because it relies on a wide range of known and unknown variables. Many approaches, including technical analysis, fundamental analysis, time series analysis, and statistical analysis are used to attempt to predict the share price; however, none of these methods has been demonstrated to be a consistently effective prediction tool. Artificial neural networks (ANNs), a subfield of artificial intelligence, are one of the most modern and promising methods for resolving financial issues, such as categorizing corporate bonds and anticipating stock market indexes and bankruptcy (AI). Artificial neural networks (ANN) are a prominent technology used to forecast the future of the stock market. In order to understand financial time series, it is often essential to extract relevant information from enormous data sets using artificial neural networks. An outcome prediction neural network with three layers is trained using the back propagation method. Analysis shows that ANN outperforms every other prediction technique now available to academics in terms of stock market price predictions. It is concluded that ANN is a useful technique for predicting stock market movements globally

Keratin Waste: The Biodegradable Polymers

Keratins are everywhere, from being the major components of household dust to common contaminants of laboratory protein analysis. Keratin is the major structural fibrous protein belonging to the large family of structural proteins to form hair, wool, feathers, nails, and horns of many kinds of animals and has a high concentration of cysteine, 7–20% of the total amino acid residues, that form inter- and intramolecular disulfide bonds. Keratin wastes are considered as the environmental pollutants and produced mostly from the poultry farms, slaughterhouses, and leather industries. Keratin wastes are dumped, buried, used for landfilling, or incinerated and all these actions increase the threats of environmental hazards, pollution, negatively influence the public health, and increase greenhouse gases concentration. Nature has provided planet Earth with a variety of beneficial organisms. Soil is considered as a well-known source for the growth of keratinophilic microflora (fungi and bacteria), which have the capability to degrade the keratin waste. The keratin-degradation ability of keratinophilic microflora has been credited with the production of the microbial keratinase enzyme and biodegradation takes place (enzymatic degradation). So, the keratin wastes are the biodegradable polymers. Keratinase is the industrially significant enzyme that offers bioconversion of keratin waste, utilization as animal feed supplements, and dehairing agents in tannery industries and textile industries