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Research ArticleOpen accessIn the abstractFeasibility of Hybrid Neuro-Fuzzy (ANFIS) Machine Learning Model with Classical Multi-Linear Regression (MLR) For the Simulation of Solar Radiation: A Case Study Abuja, NigeriaNajashi B. Gafai, Asia'u Talatu BelgoreThe extremely variable nature of solar radiation makes it difficult for solar power plants to keep up with predicted power output and demand curves. As a result, solar radiation simulation is crucial to the efficient design, administration, and operation of any solar power plant. With only partially satisfactory results, empirical models have been routinely employed in Nigeria to predict solar … …Energy Research Journal, Vol. 13, Issue 1 · 21 Jul 2022 · 10,037 accessesView PDFCite
Research ArticleOpen accessIn the abstractIraqi Stock Market Prediction using Proposed Model of Convolution Neural NetworkSama Hayder Abdulhussein, Nashaat Jasim Al-Anber, Hayfaa Abdulzahra AteeThe stock market, sometimes known as the share market, is a marketplace for stock sellers and buyers. A stock exchange is defined as a mechanism through which stockbrokers can purchase and sell shares, bonds, and other assets. Many businesses, regardless of their industries or domains, make their shares or stocks available on the stock exchange. For value investors, predicting the … …Journal of Computer Science, Vol. 18, Issue 5 · 23 May 2022 · 6,537 accessesView PDFCite
Research ArticleOpen accessIn the abstractModification of the Ornstein Uhlenbeck Process to Incorporate the Influence of Speculation on Volatility in Financial MarketsHendrietha Joan Hendricks, Jacob Ongala, Dismas NtirampebaFinancial market participants often speculate on how markets would behave in the light of certain information at hand. This speculation contributes to volatility within the financial market and consequently, it makes the market unstable. The Ornstein Uhlenbeck (OU) model has intensively been used in modelling volatility, however, the contribution of speculation on volatility has not been studied in the OU … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 18 Jan 2022 · 7,178 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Handling of Medical Data Classification in Cloud-Edge Network using Optimization AlgorithmS. S. Saranya, N. Sabiyath FatimaNowadays, a cloud-edge computing framework with IoT offers different medicinal facilities by classifying a massive amount of patients’ health data through a Deep Neural Network. But, how to optimize task scheduling while carrying multiple tasks from multiple edge devices in real-time was still challenging. This article introduces a cooperative cloud-edge computing structure to effectively perform the fuzzy DNN classification into … …Journal of Computer Science, Vol. 17, Issue 11 · 30 Nov 2021 · 6,486 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock price prediction using Generative Adversarial NetworksHungChun Lin, Chen Chen, GaoFeng Huang, Amir JafariDeep learning is an exciting topic. It has been utilized in many areas owing to its strong potential. For example, it has been widely used in the financial area which is vital to the society, such as high-frequency trading, portfolio optimization, fraud detection and risk management. Stock market prediction is one of the most popular and valuable areas in finance. … …Journal of Computer Science, Vol. 17, Issue 3 · 2 Apr 2021 · 17,714 accessesView PDFCite
Review ArticleOpen accessIn the abstractThe use of Principal Component Regression and Time Series Analysis to Predict Nitrous Oxide Emissions in GhanaBenjamin Odoi, Lewis Brew, Christopher AttafuahThe disturbing pace of emanation of Nitrous Oxide (N2O) into the atmosphere and its calamitous impact on the environment, as monitored by many governmental agencies and researchers has become a wellspring of worry for many nations and therefore needs due attention. The study deployed nitrous oxide emissions from the three sectors to the total nitrous oxide emissions in Ghana over … …Energy Research Journal, Vol. 12, Issue 1 · 6 Jan 2021 · 8,598 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,323 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT Framework for Smart Irrigation using Machine Learning TechniqueS. Ramya, A.M. Swetha, Manivannan DoraipandianThe scarcity of freshwater around the world is becoming a serious issue, so there is a dire need to come up with a solution for effective utilization of water resources. Basically, agriculture depends on monsoon which is not a sufficient water source. The Internet of Things (IoT) and Machine Learning (ML) based smart irrigation system is employed in the field … …Journal of Computer Science, Vol. 16, Issue 3 · 26 Mar 2020 · 9,661 accessesView PDFCite
Research ArticleOpen accessIn the abstractSolving Multi-Objective Master Production Scheduling Model of Kalak Refinery System Using Hybrid Evolutionary Imperialist Competitive AlgorithmShereen Saleem Sadiq, Adnan Mohsin Abdulazeez, Habibollah HaronThe improvement of operational planning in the field of oil refinery management is becoming increasingly essential and valid. The influential primary factor, among others, is the ever-changing economic climate. The industry must continually assess the potential impacts of variations in the final product demand, price fluctuations, crude oil compositions and even seek out immediate opportunities within the market. The Master … …Journal of Computer Science, Vol. 16, Issue 2 · 12 Feb 2020 · 7,834 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Artificial Neural Network Model for Option PricingHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiIn the absence of a well-defined input selection technique associated with the pure ANN models, Option pricing using pure ANN models while relaxing the assumption of constant volatility remains a challenge. The conservative drill espoused has been to make allowances for a large number of input lags with the confidence that the ability of ANN to integrate suppleness and redundancy … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 8 Aug 2019 · 7,415 accessesView PDFCite