Search Results

Over the past decade, Bitcoin’s unprecedented performance has underscored its po-sition as the premier asset class. Starting from an insignificant value and reaching an astounding high of around 65,000 U.S dollars in 2021 – all without a central con-trolling authority – Bitcoin’s trajectory is undoubtedly a historical feat. Its intangible nature, initially a subject of…

The intention of this research is to study and design an automated agriculture commodity price prediction system with novel machine learning techniques. Due to the increasing large amounts historical data of agricultural commodity prices and the need of performing accurate prediction of price fluctuations, the solution has largely shifted from statistical methods to machine learning…

Forecasting food prices play an important role in livestock and agriculture to maximize profits and minimizing risks. An accurate food price prediction model can help the government which leads to optimization of resource allocation. This paper uses ridge regression as an approach for forecasting with many predictors that are related to the target variable. Ridge…

Forecasting the gold price movement’s volatility has essential applications in areas such as risk management, options pricing, and asset allocation. The multivariate model is expected to generate more accurate forecasts than univariate models in time series data like gold prices. Multivariate analysis is based on observation and analysis of more than one statistical variable at…

This paper examines the impacts of the COVID-19 pandemic and selected commodity variables on Booking.com share price using the Markov-switching approach. Daily data spans from January 2017 through July 2020 are utilized in this study. Empirical evidence showed that COVID-19, international crude oil price, and gold price affected the Booking.com share price significantly. A positive…

Global changes caused by the IV Industrial revolution and globalization processes resulted in a redistribution of roles of participants in innovative infrastructures of countries. Universities are leading both in terms of generating R&D products and in terms of developing business activities. Now there is a problem of insufficient methodological support of technological universities for pricing…

In recent years, deep learning has been widely used for time series prediction. Deep learning model that is most often used for time series prediction is LSTM. LSTM is widely used because of its excellence in remembering very long sequences. However, doing training on models that use LSTM requires a long time. Trying from one…

The power market in China is faced with problems such as the continuous widening of terminal load peak-valley difference and the imbalance between supply and demand. Under this background, this paper to establish the mathematical model of the contract price of active demand response. The first is to consider the load component of the user’s…

This paper deals about an application of optimal power flows (OPF) constrained with synchronous generator capability curve for power market analysis (SGCC). OPF main features gather in its mathematical formulation non-convexity, non-linearity, and it shows to be a hard to solve optimization problem. In some operational scenarios, SGCC can limit power flows bringing the theoretical…

This study presents a novel alternative to traditional Net Energy Metering (NEM) by proposing a set of innovative pricing schemes for solar customers participating in utility-led grid service programs through the aggregation of Distributed Energy Resources (DERs). Grounded in cooperative game theory, the proposed framework facilitates equitable and efficient value allocation among key stakeholders, namely…

Machine learning-based predictive models often face challenges, particularly biases and a lack of trust in their predictions when deployed by individual agents. Establishing a robust deployment methodology that supports validating the accuracy and fairness of these models is a critical endeavor. In this paper, we introduce a novel approach to deploying predictive models, such as…

To this extent, the delineation of techno-economic evaluations for transformers becomes more intricate through a lens of Distributed Solar Photovoltaic (DSPV) market in South Africa. Essentially, the transformer price and loss evaluation techniques should be tailored for calculating the Total Ownership Cost (TOC) of transformers facilitating decentralized energy systems. In South Africa, the traditional coal…

The fight against poverty in the Peruvian Andes is a complex task in which various professionals, such as engineers, economists, anthropologists, among others, participate. The uncertainty of the decisions taken today, no matter how appropriate they may seem, such as million-dollar investments in irrigation infrastructure, can result in over-production and, therefore, in economic recessions. For…

Piezoelectric energy harvesters (PEH) can be used in many areas of application, including human walking, railways, pavements and bridges. Piezoelectric energy harvesters are currently based on two types of external forces, namely pressure load and mechanical oscillation or vibration. A vibration energy harvesting (VEH) is a mechanical oscillation in a piezoelectric energy harvester that harvested…

This work presents an innovative solution for parking-sharing of private institutions based on daily occupancy patterns and using different real time tracking methods of vacant parking slots. The research objective consists in finding the most accurate cars detection method, for determining of vacant parking slots and updating them on application web page. Beside the technical…

The crisis linked to the COVID-19 and the uncertainty it generates in the unprecedented health, societal, economic and financial fields have had a strong impact on the stock markets. Indeed, in such a climate of very high uncertainty, it is to be expected that the excessive stock market price movements will continue, with both declines…

With the current emerging development pattern in Malaysia, E-Government has been unveiled by the Malaysian Government to be one of the multimedia super corridor flagship applications to implement digital technology to improve government operations. E-procurement was originally utilized by businesses to minimize turnaround times and prices, but recently it was often used as a platform…

Obstacles, both imagined and real, continue to hinder the wider adoption of Education 4.0 learning technologies although these technologies are available in the mainstream consumer market. At the same time, the boom in Industry 4.0 manufacturing has brought down the prices of these technological tools making them generally more affordable. A case in point is…

Photovoltaic systems and monitoring go hand in hand. There is no better way to check the health of your photovoltaic system than to utilize a remote monitoring system. Monitoring and tracking of photovoltaic systems are crucial for reliable functioning and optimal yield of any solar electric system. This paper aims to introduce a remote electronic…

In an enterprise Wifi network, indoor and dense, co-channel interference is a major issue. Wifi controllers help tackle this problem thanks to radio resource management (RRM). RRM is a fundamental building block of any controller functional architecture. One aim of RRM is to process the radio plan such as to maximize the overall network transmit…

Peer-to-peer (P2P) energy trading is a mechanism that allows people to share locally the energy they have generated from distributed renewable resources (DER), to generate profit form the unused resources and to reduce the cost for electricity for the household and in the community itself. This calls for the design of new energy markets, accompanied…

This paper is proposed to build a model by applying two methods, namely support vector machine and nonnegative matrix factorization in the process of predicting stock market movement using twitter and historical data. The stock exchange is based on the LQ 45 stock with period from August 2018 – January 2019. The features consist of…

Consumers of electrical energy have looked more closely to the energy consumption in last years due to the successive increase of the electricity bill. Nowadays it is possible to notice that many consumers have been looking for ways to reduce their consumption or the value of their electricity bill. Such a cost reduction is obtained…

Climate change, increasing fuel oil prices and new international regulation on ship emissions lead to more focus on shipping fuel consumption and energy efficiency. There are various solutions for improving the ship energy efficiency. In this manuscript, we aim to present a real case of energy saving by adopting the central cooling system with box…

Currently the use of distributed energy resources, especially renewable generation, and demand response programs are widely discussed in scientific contexts, since they are a reality in nowadays electricity markets and distribution networks. In order to benefit from these concepts, an efficient energy management system is needed to prevent energy wasting and increase profits. In this…