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Search Results (114)
  • Open Access

    ARTICLE

    Hybrid Evolutionary Algorithm Based Relevance Feedback Approach for Image Retrieval

    Awais Mahmood1,*, Muhammad Imran2, Aun Irtaza3, Qammar Abbas4, Habib Dhahri1,5, Esam Mohammed Asem Othman1, Arif Jamal Malik6, Aaqif Afzaal Abbasi6

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 963-979, 2022, DOI:10.32604/cmc.2022.019291 - 07 September 2021

    Abstract Searching images from the large image databases is one of the potential research areas of multimedia research. The most challenging task for nay CBIR system is to capture the high level semantic of user. The researchers of multimedia domain are trying to fix this issue with the help of Relevance Feedback (RF). However existing RF based approaches needs a number of iteration to fulfill user's requirements. This paper proposed a novel methodology to achieve better results in early iteration to reduce the user interaction with the system. In previous research work it is reported that… More >

  • Open Access

    ARTICLE

    Stock Prediction Based on Technical Indicators Using Deep Learning Model

    Manish Agrawal1, Piyush Kumar Shukla2, Rajit Nair3, Anand Nayyar4,5,*, Mehedi Masud6

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 287-304, 2022, DOI:10.32604/cmc.2022.014637 - 07 September 2021

    Abstract Stock market trends forecast is one of the most current topics and a significant research challenge due to its dynamic and unstable nature. The stock data is usually non-stationary, and attributes are non-correlative to each other. Several traditional Stock Technical Indicators (STIs) may incorrectly predict the stock market trends. To study the stock market characteristics using STIs and make efficient trading decisions, a robust model is built. This paper aims to build up an Evolutionary Deep Learning Model (EDLM) to identify stock trends’ prices by using STIs. The proposed model has implemented the Deep Learning… More >

  • Open Access

    ARTICLE

    New Solution Generation Strategy to Improve Brain Storm Optimization Algorithm for Classification

    Yu Xue1,2,* , Yan Zhao1

    Journal on Internet of Things, Vol.3, No.3, pp. 109-118, 2021, DOI:10.32604/jiot.2021.014980 - 16 December 2021

    Abstract As a new intelligent optimization method, brain storm optimization (BSO) algorithm has been widely concerned for its advantages in solving classical optimization problems. Recently, an evolutionary classification optimization model based on BSO algorithm has been proposed, which proves its effectiveness in solving the classification problem. However, BSO algorithm also has defects. For example, large-scale datasets make the structure of the model complex, which affects its classification performance. In addition, in the process of optimization, the information of the dominant solution cannot be well preserved in BSO, which leads to its limitations in classification performance. Moreover,… More >

  • Open Access

    ARTICLE

    A Reliability Evaluation Method for Intermittent Jointed Rock Slope Based on Evolutionary Support Vector Machine

    Shuai Zheng, An-Nan Jiang*, Kai-Shuai Feng

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 149-166, 2021, DOI:10.32604/cmes.2021.016761 - 24 August 2021

    Abstract The randomness of rock joint development is an important factor in the uncertainty of geotechnical engineering stability. In this study, a method is proposed to evaluate the reliability of intermittent jointed rock slope. The least squares support vector machine (LSSVM) evolved by a bacterial foraging optimization algorithm (BFOA) is used to establish a response surface model to express the mapping relationship between the intermittent joint parameters and the slope safety factor. The training samples are obtained from the numerical calculation based on the joint finite element method during this process. Considering the randomness of the… More >

  • Open Access

    ARTICLE

    An Optimized Convolutional Neural Network Architecture Based on Evolutionary Ensemble Learning

    Qasim M. Zainel1, Murad B. Khorsheed2, Saad Darwish3,*, Amr A. Ahmed4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3813-3828, 2021, DOI:10.32604/cmc.2021.014759 - 24 August 2021

    Abstract Convolutional Neural Networks (CNNs) models succeed in vast domains. CNNs are available in a variety of topologies and sizes. The challenge in this area is to develop the optimal CNN architecture for a particular issue in order to achieve high results by using minimal computational resources to train the architecture. Our proposed framework to automated design is aimed at resolving this problem. The proposed framework is focused on a genetic algorithm that develops a population of CNN models in order to find the architecture that is the best fit. In comparison to the co-authored work,… More >

  • Open Access

    ARTICLE

    A Hybrid Algorithm Based on PSO and GA for Feature Selection

    Yu Xue1,*, Asma Aouari1, Romany F. Mansour2, Shoubao Su3

    Journal of Cyber Security, Vol.3, No.2, pp. 117-124, 2021, DOI:10.32604/jcs.2021.017018 - 02 August 2021

    Abstract One of the main problems of machine learning and data mining is to develop a basic model with a few features, to reduce the algorithms involved in classification’s computational complexity. In this paper, the collection of features has an essential importance in the classification process to be able minimize computational time, which decreases data size and increases the precision and effectiveness of specific machine learning activities. Due to its superiority to conventional optimization methods, several metaheuristics have been used to resolve FS issues. This is why hybrid metaheuristics help increase the search and convergence rate More >

  • Open Access

    ARTICLE

    An Evolutionary Algorithm for Non-Destructive Reverse Engineering of Integrated Circuits

    Huan Zhang1,2, Jiliu Zhou1,2,*, Xi Wu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 1151-1175, 2021, DOI:10.32604/cmes.2021.015462 - 24 May 2021

    Abstract In hardware Trojan detection technology, destructive reverse engineering can restore an original integrated circuit with the highest accuracy. However, this method has a much higher overhead in terms of time, effort, and cost than bypass detection. This study proposes an algorithm, called mixed-feature gene expression programming, which applies non-destructive reverse engineering to the chip with bypass detection data. It aims to recover the original integrated circuit hardware, or else reveal the unknown circuit design in the chip. More >

  • Open Access

    ARTICLE

    External Incentive Mechanism Research on Knowledge Cooperation-Sharing in the Chinese Creative Industry Cluster

    Changchun Gao1, Shiyu Liu1,*, Chenhui Yu1, Peng Guo2

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 365-379, 2021, DOI:10.32604/csse.2021.016506 - 19 May 2021

    Abstract The creative industry is a knowledge-based industry, but it is difficult and complex to create knowledge for enterprises. The principle of cooperation-sharing posits that companies’ limited resources prohibit them from gaining a competitive advantage in all business areas. Therefore, cooperation-sharing can help businesses overcome this hurdle. Cooperation-sharing expedites economic development, breaks the barrier of independent knowledge creation, and enhances resource utilization. However, the effectiveness and stability of knowledge cooperation-sharing are key problems facing governments and other regulators. This study can help regulators promote honesty in enterprise cooperation-sharing. Based on the hypothesis of bounded rationality, the… More >

  • Open Access

    ARTICLE

    Improving Network Longevity in Wireless Sensor Networks Using an Evolutionary Optimization Approach

    V. Nivedhitha1,*, A. Gopi Saminathan2, P. Thirumurugan3

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 603-616, 2021, DOI:10.32604/iasc.2021.016780 - 20 April 2021

    Abstract Several protocols strive to improve network longevity but fail to ameliorate the uneven overhead imparted upon the sensor nodes that lead to temporal deaths. The proposed work uses a metaheuristic approach that promotes load balancing and energy-efficient data transmission using the fruit fly optimization algorithm (FFOA). The approach combines the LEACH protocol with differential evolution (DE) to select an optimum cluster head in every cluster. The algorithm is designed to provide energy-efficient data transmissions based on the smell and vision foraging behavior of fruit flies. The approach considers the compactness of nodes, energy capacity, and More >

  • Open Access

    ARTICLE

    Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

    Farhan Aadil1, Bilal Mehmood1, Najam Ul Hasan2, Sangsoon Lim3,*, Sadia Ejaz1, Noor Zaman4

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2499-2513, 2021, DOI:10.32604/cmc.2021.014647 - 13 April 2021

    Abstract A wireless body area network (WBAN) consists of tiny health-monitoring sensors implanted in or placed on the human body. These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things (IoT) systems. WBANs are connected to medical servers that monitor patients’ health. This type of network can protect critical patients’ lives due to the ability to monitor patients’ health continuously and remotely. The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely. However, during patient movement, the WBAN patient nodes… More >

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