In this paper, we propose a novel approach to optimize parameters for strategies in automated trading systems. Based on the framework of Reinforcement learning, our work includes the development of a learning environment, state representation, reward...
In this work, we explore the application of deep reinforcement learning (DRL) to algorithmic trading. While algorithmic trading is focused on using computer algorithms to automate a predefined trading strategy, in this work, we train a Double Deep Q-...
Energy management systems (EMSs) are regarded as essential components within smart grids. In pursuit of efficiency, reliability, stability, and sustainability, an integrated EMS empowered by machine learning (ML) has been addressed as a promising sol...
In recent years, computational intelligence techniques have significantly contributed to the automation and optimization of trading strategies. Despite the increasing sophistication of predictive models, classical technical indicators such as dual Si...
Many tasks in a modern household are performed by machines, e.g., a dishwasher or a vacuum cleaner, and in the near future most household tasks will be performed by smart service robots. This will relieve the residents, who in turn can enjoy their fr...
Reliable access to electricity is still a challenge in many developing countries. Indeed, rural areas in sub-Saharan Africa and developing countries such as India still encounter frequent power outages. Local energy markets (LEMs) have emerged as a l...
Predicted price-to-book value ratios (P/BV) are widely used for the valuation of listed common stocks. However, with the application of automated trading system (ATS), the existing indicators that are applied in the method are losing their effectiven...
Individual investors often struggle to predict stock prices due to the limitations imposed by the computational capacities of personal laptop Graphics Processing Units (GPUs) when running intensive deep learning models. This study proposes solving th...
There are several automated stock trading programs using reinforcement learning, one of which is an ensemble strategy. The main idea of the ensemble strategy is to train DRL agents and make an ensemble with three different actor–critic algorith...
In this research, we attempted to fit a trading system based on polynomial moving regression bands (MRB) to Nasdaq100 stocks from 2017 till the end of March 2024. Since stocks movement does not follow a linear behavior, we used multiple degree polyno...
Integrated energy systems (IESs) couple multiple energy sources to promote clean energy and reduce emissions. IESs need to participate in business activities, such as power trading, aided by automated data-driven systems to achieve optimal and econom...
The integration of renewable energy sources (RES) and distributed energy resources (DER) into local energy markets is transforming modern power grids toward a decentralized architecture. To enhance the efficiency of decentralized energy trading, bloc...
Grid algorithmic trading has become quite popular among traders because it shows several advantages with respect to similar approaches. Basically, a grid trading strategy is a method that seeks to make profit on the market movements of the underlying...
Algorithmic trading has become the standard in the financial market. Traditionally, most algorithms have relied on rule-based expert systems which are a set of complex if/then rules that need to be updated manually to changing market conditions. Mach...
This research investigates the integration of blockchain technology into smart grids, focusing on optimizing both electrical billing and peer-to-peer energy trading between producers and consumers. Using blockchain smart contracts, the system automat...
To combat the problem of illegal access to a service, several location proof strategies have been proposed in the literature. In blockchain-based decentralized applications, transactions can be issued by IoT nodes or other automated smart devices. Ke...
Currently, there are several issues in China’s rural property rights trading, including poor credit reporting, low transaction efficiency, non-standardized transaction contracts, and high costs for rights protection. However, blockchain technol...
The architecture of cloud–edge collaboration can improve the efficiency of Internet of Things (IoT) systems. Recent studies have pointed out that using IoT terminal devices as destinations for computing offloading can promote further optimized...
The promising power-to-gas (P2G) technology makes it possible for wind farms to absorb carbon and trade in multiple energy markets. Considering the remoteness of wind farms equipped with P2G systems and the isolation of different energy markets, the...
The Internet of things has revolutionized various domains, such as healthcare and navigation systems, by introducing mission-critical capabilities. However, the untapped potential of IoT in the energy sector is a topic of contention. Shifting from tr...
In the global trend towards decarbonization, peer-to-peer (P2P) energy trading is garnering increasing attention. Furthermore, energy management on the demand side plays a crucial role in decarbonization efforts. The authors have previously developed...
Blockchain-based financial ecosystems generate unprecedented volumes of multi-temporal data streams requiring sophisticated analytical frameworks that leverage both on-chain transaction patterns and off-chain market microstructure dynamics. This stud...
Blockchain technology (BCT) enables the automated execution of smart contracts in peer-to-peer (P2P) energy trading. BCT-based P2P platforms allow the sharing, exchange and trade of energy among consumers or prosumers as peers, fostering the decarbon...
The introduction of Smart Meter Gateways (SMGWs) to buildings and households creates new opportunities and challenges for energy management systems. While SMGWs provide interfaces for accessing recorded information and enable communication to externa...
The development of local energy communities observed in the last years requires the reorganization of energy consumption and production. In these newly considered energy systems, the commercial and technical decision processes should be decentralized...
This article provides an in-depth analysis of blockchain research in the energy sector, focusing on projects funded by the U.S. Department of Energy (DOE) and comparing them with industry-funded initiatives. A total of 110 funded activities within th...
This research presents an innovative blockchain-based solution for the charging and energy trading of electric vehicles (EVs). By combining the strengths of two prominent consensus mechanisms, Proof of Work (PoW) and Proof of Stake (PoS), the propose...
In this paper, we investigate how systemic errors due to random sampling impact on automated algorithm selection for bound-constrained, single-objective, continuous black-box optimization. We construct a machine learning-based algorithm selector, whi...
This paper evaluates the suitability of blockchain technology for the Article 6.2 carbon market mechanism of the Paris Agreement. The bottom-up approach of the Paris Agreement causes challenges to the robust accounting of mitigation outcomes and info...
The reliable operation of photovoltaic (PV) systems is essential for sustainable energy production, yet their efficiency is often compromised by defects such as bird droppings, cracks, and dust accumulation. Automated defect detection is critical for...
We propose a mathematical model of momentum risk-taking, which is essentially real-time risk management focused on short-term volatility. Its implementation, a fully automated momentum equity trading system, is systematically discussed in this paper....
The global expansion of road networks and the aging of infrastructure have intensified the need for efficient pavement distress detection technologies to ensure road safety and sustainability. While traditional manual inspections are time consuming a...
Water availability is increasingly stressed in cities across the world due to population growth, which increases demands, and climate change, which can decrease supply. Novel water markets and water supply paradigms are emerging to address water shor...
Immunological principles can be used to build a sustainable investment portfolio. The theory of immunology states that information about recognized pathogens is stored in the memory of the immune system. Information about previous illnesses can be he...
The current formal common denominator of the electricity supply system in Europe has been the Harmonized Electricity Market Role Model (HEMRM) set up by ENTSO-E, ebIX, and EFET at the turn of the millennium; it introduced the concept of de-coupling a...
Stock trading faces significant challenges due to market volatility and the complexity of integrating diverse data sources, such as financial texts and numerical market data. This paper proposes an innovative automated trading system that integrates...
Indoor localization is becoming increasingly important but is not yet widespread because installing the necessary infrastructure is often time-consuming and labor-intensive, which drives up the price. This paper presents an automated indoor localizat...
The application of artificial intelligence enhances the ability of sensor and networking technologies to realize smart systems that sense, monitor and automatically control our everyday environments. Intelligent systems and applications often automat...
Forecasting the behavior of the stock market is a classic but difficult topic, one that has attracted the interest of both economists and computer scientists. Over the course of the last couple of decades, researchers have investigated linear models...
Decentralized energy trading has been designed as a scalable substitute for traditional electricity markets. While blockchain technology facilitates efficient transparency and automation for peer-to-peer energy trading, the majority of current propos...
Internet of Things (IoT)-based devices, especially those used for home automation, consist of their own sensors and generate many logs during a process. Enterprises producing IoT devices convert these log data into more useful data through secondary...
Since conventional eco approach systems can only achieve longitudinal automation, they may be disabled due to the impedance of the slow-moving vehicle. In addition, they could sacrifice a lot in travel time and it is hard to control the articulated t...
Maritime operations play a critical role in global trade but face persistent safety challenges due to human error, environmental factors, and operational complexities. This review explores the transformative potential of Large Language Models (LLMs)...
Seaports are at the forefront of global trade networks, serving as hubs for maritime logistics and the transportation of goods and people. To meet the requirements of such networks, seaport authorities are investing in advanced technologies to enhanc...
Bus company operators are interested in obtaining knowledge about the number of passengers on their buses—preferably doing so at low deployment costs and in an automated manner, while keeping accuracy high. One solution, widely used in practice...
In this study, we adopt a geometallurgical analytical approach common in mineral processing in the characterization of samples of shredded waste printed circuit board (PCB) E-waste, originating from Europe. Conventionally, bulk chemical analysis prov...
Reactive and biased human decision-making during well construction operations can result in problems ranging from minor inefficiencies to events that can have far-reaching negative consequences for safety, environmental compliance and cost. A system...
Motivated by the recent blockchain technology originally built for bitcoin transactions, various industries are exploring the opportunities to redefine their existing operational systems. In this study, an innovative environmentally sustainable solut...
Detecting animals to estimate abundance can be difficult, particularly when the habitat is dense or the target animals are fossorial. The recent surge in the use of thermal imagers in ecology and their use in animal detections can increase the accura...
Pick-and-place handling of aquatic products (e.g., raw oyster) in packing processing remains manual, despite advances in soft robotic grippers as well as robotic systems that offer a path to automation in food production lines. In this study, we focu...
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