Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System

Ko, Hoon; Rim, KwangCheol; Praça, Isabel

doi:10.3390/s21124237

Cited by 5 publications

(6 citation statements)

References 15 publications

(20 reference statements)

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“…This process can be generalized by a general model of communication systems. Figure 6 is a communication system model [20].…”

Section: R E T R a C T E Dmentioning

confidence: 99%

Radio Resource Allocation Algorithm of the M2M Communication System in 5G Era

She

2022

Wireless Communications and Mobile Computing

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M2M is a concept and a general term for all technologies that enhance the communication and network capabilities of machines and equipment. It is a combination of different types of communication technologies. M2M enables all devices and users to share information, saving operation time and improving work efficiency. M2M is not a simple data transmission, but it is an intelligent and interactive communication between machines. Even if no real-time signal is sent, the machine will actively communicate according to the established program and select intelligently according to the obtained data. The communication system refers to the general term of the technology that completes the information transmission function. The modern communication system is mainly realized by the propagation of electromagnetic waves in free space or the transmission mechanism in the guiding medium. When the wavelength of the electromagnetic wave reaches the light wave range, such a telecommunication system is called an optical communication system, and the communication system in the other electromagnetic wave range is called an electromagnetic communication system, abbreviated as a telecommunication system. The purpose of this paper is to explore the study of wireless data sharing method for M2M mobile telecommunication systems in the 5G era. It is expected that the new algorithm will make the wireless resource allocation more reasonable and improve the resource utilization rate. The performance of the deterministic measurement matrix proposed in this paper is close to or even better than that of the random measurement matrix. The M-SP algorithm greatly improves the performance of the SP algorithm. The experimental results of this paper show that when the number of microbase stations is 10, the energy consumption of the direct algorithm is 175000 W, the energy consumption of the indirect algorithm is 350000 W, and the energy consumption of the direct algorithm is much smaller than that of the indirect algorithm.

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“…This process can be generalized by a general model of communication systems. Figure 6 is a communication system model [20].…”

Section: R E T R a C T E Dmentioning

confidence: 99%

Radio Resource Allocation Algorithm of the M2M Communication System in 5G Era

She

2022

Wireless Communications and Mobile Computing

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“…The attenuation of speech signal is the phenomenon of low frequency, large delay, and instability when the sound intensity exceeds the power emitted by the speech signal under a specific condition, or below this threshold. This sound is easy to be ignored and produces noise pollution ( Zhang et al, 2017 ; Dartmann et al, 2019 ; Ko et al, 2021 ). Therefore, the first-order digital filter is usually used to adjust the weight of signal processing to improve the characteristics of voice information in the high-frequency part.…”

Section: Discussion On the Integration Of Financial Self-service Term...mentioning

confidence: 99%

Integrated Design of Financial Self-Service Terminal Based on Artificial Intelligence Voice Interaction

Chen

Chen²,

Zhao

2022

Front. Psychol.

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Integrated design of financial self-service terminal based on artificial intelligence voice interaction with the rapid development of science and technology, artificial intelligence technology is deepening in the field of intelligence and automation. The financial industry is the lifeblood of a country’s economy, with great growth potential and high growth rate. The integrated design of intelligent financial self-service terminal has become an important topic in the field of rapid development of social economy and science and technology. Therefore, this paper designs the integration of financial self-service terminal based on artificial intelligence voice interaction. First, this paper introduces the meaning and composition of financial self-service terminal integration, then studies the voice interaction principle based on artificial intelligence technology, and designs the integrated structure of financial self-service terminal with voice interaction. After that, this paper makes a series of tests on voice interaction technology, user experience, and the performance of financial self-service terminal. Finally, the test results of voice interaction are as follows: the delay estimation results of voice interaction of the terminal are relatively accurate, and the error points are basically within five sampling points, which indicate that the delay estimation algorithm is practical. The endpoint detection method based on CO complexity can effectively overcome the impact of noise environment on speech endpoint detection system and is suitable for the requirements of robust speech recognition system. Considering that the actual application scenario of voice positioning can judge the speaker’s position and turn to the speaker’s direction during human–computer interaction, the azimuth error is acceptable within a few degrees to meet the application requirements. The direction angle error is acceptable within a few degrees to meet the application requirements. The accuracy of the improved algorithm is improved in intercepting effective speech signals. The terminal has short running time and delay time, small memory, and central processing unit (CPU) occupation and can meet the needs of users. The speech recognition accuracy of the financial self-service terminal basically reaches more than 80%, which can basically meet the daily needs.

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“…In other words, in our solution, the energy provider has only its conventional energy sources, and it may buy RECs when the energy from its own sources is not sufficient to meet the energy supply of the consumers at a given time. In our proposal, similar to [ 6 ], we consider that the consumers have a smart energy agent (SEA), which is a type of smart meter with the capability of communicating with other SEAs when it comes to trade energy. Additionally, we assume that an SEA allows not only a consumer to make the energy request but can also autonomously make an energy request to the energy broker if it is authorized by the consumer.…”

Section: Proposed Demand-based Trading Mechanism With Dynamic Pricing Model Of Renewable Energy Sourcesmentioning

confidence: 99%

“…Therefore, this brings about the necessity of an energy broker, which allows to trade energy among DERs [ 4 ]. In order to manage energy use and trade efficiently, the IoT-based smart agents [ 5 , 6 ] can facilitate communication between these DERs and the energy broker, thereby allowing sharing information (e.g., energy generation and consumption information). In addition, when these smart agents are applied, new DERs can be added to the consumer side with the existing deployed DERs without modification of operation (e.g., grid connected mode/isolated mode) [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Energy Trading among Power Grid and Renewable Energy Sources: A Dynamic Pricing and Demand Scheme for Profit Maximization

Yoo

Jeon

Newaz

et al. 2021

Sensors

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With the technical growth and the reduction of deployment cost for distributed energy resources (DERs), such as solar photovoltaic (PV), energy trading has been recently encouraged to energy consumers, which can sell energy from their own energy storage system (ESS). Meanwhile, due to the unprecedented rise of greenhouse gas (GHG) emissions, some countries (e.g., Republic of Korea and India) have mandated using a renewable energy certificate (REC) in energy trading markets. In this paper, we propose an energy broker model to boost energy trading between the existing power grid and energy consumers. In particular, to maximize the profits of energy consumers and the energy provider, the proposed energy broker is in charge of deciding the optimal demand and dynamic price of energy in an REC-based energy trading market. In this solution, the smart agents (e.g., IoT intelligent devices) of consumers exchange energy trading associated information, including the amount of energy generation, price and REC. For deciding the optimal demand and dynamic pricing, we formulate convex optimization problems using dual decomposition. Through a numerical simulation analysis, we compare the performance of the proposed dynamic pricing strategy with the conventional pricing strategies. Results show that the proposed dynamic pricing and demand control strategies can encourage energy trading by allowing RECs trading of the conventional power grid.

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Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System

Cited by 5 publications

References 15 publications

Radio Resource Allocation Algorithm of the M2M Communication System in 5G Era

Radio Resource Allocation Algorithm of the M2M Communication System in 5G Era

Integrated Design of Financial Self-Service Terminal Based on Artificial Intelligence Voice Interaction

Energy Trading among Power Grid and Renewable Energy Sources: A Dynamic Pricing and Demand Scheme for Profit Maximization

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