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  • Open Access


    Stock Market Prediction Using Generative Adversarial Networks (GANs): Hybrid Intelligent Model

    Fares Abdulhafidh Dael1,*, Ömer Çağrı Yavuz2, Uğur Yavuz1

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 19-35, 2023, DOI:10.32604/csse.2023.037903

    Abstract The key indication of a nation’s economic development and strength is the stock market. Inflation and economic expansion affect the volatility of the stock market. Given the multitude of factors, predicting stock prices is intrinsically challenging. Predicting the movement of stock price indexes is a difficult component of predicting financial time series. Accurately predicting the price movement of stocks can result in financial advantages for investors. Due to the complexity of stock market data, it is extremely challenging to create accurate forecasting models. Using machine learning and other algorithms to anticipate stock prices is an interesting area. The purpose of… More >

  • Open Access


    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Shehab Abdulhabib Alzaeemi1, Kim Gaik Tay1,*, Audrey Huong1, Saratha Sathasivam2, Majid Khan bin Majahar Ali2

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1163-1184, 2023, DOI:10.32604/csse.2023.038912

    Abstract Radial Basis Function Neural Network (RBFNN) ensembles have long suffered from non-efficient training, where incorrect parameter settings can be computationally disastrous. This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. Inspired by evolutionary algorithms, which can iteratively find the near-optimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN-2SAT). The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA),… More >

  • Open Access


    Higher Order OAM Mode Generation Using Wearable Antenna for 5G NR Bands

    Shehab Khan Noor1, Arif Mawardi Ismail1, Mohd Najib Mohd Yasin1,*, Mohamed Nasrun Osman1, Thennarasan Sabapathy1, Shakhirul Mat Salleh2, Ping Jack Soh3, Ali Hanafiah Rambe4, Nurulazlina Ramli5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 537-551, 2023, DOI:10.32604/csse.2023.037381

    Abstract This paper presents a flexible and wearable textile array antenna designed to generate Orbital Angular Momentum (OAM) waves with Mode +2 at 3.5 GHz (3.4 to 3.6 GHz) of the sub-6 GHz fifth-generation (5G) New Radio (NR) band. The proposed antenna is based on a uniform circular array of eight microstrip patch antennas on a felt textile substrate. In contrast to previous works involving the use of rigid substrates to generate OAM waves, this work explored the use of flexible substrates to generate OAM waves for the first time. Other than that, the proposed antenna was simulated, analyzed, fabricated, and… More >

  • Open Access


    Optimal Operation of Distributed Generations Considering Demand Response in a Microgrid Using GWO Algorithm

    Hassan Shokouhandeh1, Mehrdad Ahmadi Kamarposhti2,*, William Holderbaum3, Ilhami Colak4, Phatiphat Thounthong5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 809-822, 2023, DOI:10.32604/csse.2023.035827

    Abstract The widespread penetration of distributed energy sources and the use of load response programs, especially in a microgrid, have caused many power system issues, such as control and operation of these networks, to be affected. The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid. In this paper, the optimum operation of distributed generation resources and heat and power storage in a microgrid, was performed based on real-time pricing through the proposed gray wolf optimization (GWO) algorithm to reduce the energy supply cost with the… More >

  • Open Access


    Tight Sandstone Image Augmentation for Image Identification Using Deep Learning

    Dongsheng Li, Chunsheng Li*, Kejia Zhang, Tao Liu, Fang Liu, Jingsong Yin, Mingyue Liao

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1209-1231, 2023, DOI:10.32604/csse.2023.034395

    Abstract Intelligent identification of sandstone slice images using deep learning technology is the development trend of mineral identification, and accurate mineral particle segmentation is the most critical step for intelligent identification. A typical identification model requires many training samples to learn as many distinguishable features as possible. However, limited by the difficulty of data acquisition, the high cost of labeling, and privacy protection, this has led to a sparse sample number and cannot meet the training requirements of deep learning image identification models. In order to increase the number of samples and improve the training effect of deep learning models, this… More >

  • Open Access


    Customer Churn Prediction Framework of Inclusive Finance Based on Blockchain Smart Contract

    Fang Yu1, Wenbin Bi2, Ning Cao3,4,*, Hongjun Li1, Russell Higgs5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1-17, 2023, DOI:10.32604/csse.2023.018349

    Abstract In view of the fact that the prediction effect of influential financial customer churn in the Internet of Things environment is difficult to achieve the expectation, at the smart contract level of the blockchain, a customer churn prediction framework based on situational awareness and integrating customer attributes, the impact of project hotspots on customer interests, and customer satisfaction with the project has been built. This framework introduces the background factors in the financial customer environment, and further discusses the relationship between customers, the background of customers and the characteristics of pre-lost customers. The improved Singular Value Decomposition (SVD) algorithm and… More >

  • Open Access


    Waste Heat Recovery from a Drier Receiver of an A/C Unit Using Thermoelectric Generators

    Ali Jaber Abdulhamed1,*, Aws Al-Akam1, Ahmed A. Abduljabbar2, Mohammed H. Alkhafaji3

    Energy Engineering, Vol.120, No.8, pp. 1729-1746, 2023, DOI:10.32604/ee.2023.029069

    Abstract Thermoelectric generators (TEGs) are considered promising devices for waste heat recovery from various systems. The Seebeck effect can be utilized to generate power using the residual heat emitted by the filter dryer receiver (FDR) of an air conditioning (A/C) system, which would otherwise go to waste. The study aims to build a set of thermoelectric generators (TEG) to collect the waste heat of the FDR and generate low-power electricity. A novel electrical circuit with two transformers is designed and fabricated to produce a more stable voltage for operation and charging. The thermoelectric generator (TEGs) was installed on the FDR of… More >

  • Open Access


    Simulation Analysis of Flue Gas Waste Heat Utilization Retrofit Based on ORC System

    Liqing Yan1, Jiang Liu1,2,*, Guangwei Ying3, Ning Zhang4

    Energy Engineering, Vol.120, No.8, pp. 1919-1938, 2023, DOI:10.32604/ee.2023.027546

    Abstract Recovery of waste heat from boiler flue gas is an effective way to improve energy utilization efficiency. Taking a heating station heating project as an example, the existing heating system of this heating station was analyzed for its underutilized flue gas waste heat and low energy utilization rate. Rankine cycle is an effective waste heat recovery method, and a steam boiler organic Rankine cycle (ORC) cogeneration waste heat utilization method is proposed. The system model simulation is constructed and verified. First, a thermodynamic model was constructed in MATLAB and five suitable work gases were selected to analyze the effects of… More > Graphic Abstract

    Simulation Analysis of Flue Gas Waste Heat Utilization Retrofit Based on ORC System

  • Open Access


    Distributed Robust Optimal Dispatch for the Microgrid Considering Output Correlation between Wind and Photovoltaic

    Ming Li1,*, Cairen Furifu1, Chengyang Ge2, Yunping Zheng1, Shunfu Lin2, Ronghui Liu2

    Energy Engineering, Vol.120, No.8, pp. 1775-1801, 2023, DOI:10.32604/ee.2023.027215

    Abstract As an effective carrier of integrated clean energy, the microgrid has attracted wide attention. The randomness of renewable energies such as wind and solar power output brings a significant cost and impact on the economics and reliability of microgrids. This paper proposes an optimization scheme based on the distributionally robust optimization (DRO) model for a microgrid considering solar-wind correlation. Firstly, scenarios of wind and solar power output scenarios are generated based on non-parametric kernel density estimation and the Frank-Copula function; then the generated scenario results are reduced by K-means clustering; finally, the probability confidence interval of scenario distribution is constrained… More >

  • Open Access



    Daniela Galatroa,*, Maan Al-Zareera , Carlos Da Silvaa , David A. Romeroa , Cristina H. Amona

    Frontiers in Heat and Mass Transfer, Vol.14, No.1, pp. 1-18, 2020, DOI:10.5098/hmt.14.17

    Abstract This work presents a succinct review of the thermal behavior of lithium-ion batteries (LIBs) and its relationship with aging, heat generation, thermal management and thermal failure. This work focuses on the temperature effects that promote the main aging mechanisms in the anode and compare these effects among different cell chemistries for calendar and cycling aging modes. We review the strategies to mitigate aging, including the design of the battery thermal management system (BTMS), best practices of battery users to minimize the effect of stress factors, and the appropriate selection of the anode material. We discuss the heat generation and surface… More >

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