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  • Open Access


    Feature Extraction and Classification of Plant Leaf Diseases Using Deep Learning Techniques

    K. Anitha1, S. Srinivasan2,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 233-247, 2022, DOI:10.32604/cmc.2022.026542

    Abstract In India’s economy, agriculture has been the most significant contributor. Despite the fact that agriculture’s contribution is decreasing as the world’s population grows, it continues to be the most important source of employment with a little margin of difference. As a result, there is a pressing need to pick up the pace in order to achieve competitive, productive, diverse, and long-term agriculture. Plant disease misinterpretations can result in the incorrect application of pesticides, causing crop harm. As a result, early detection of infections is critical as well as cost-effective for farmers. To diagnose the disease at an earlier stage, appropriate… More >

  • Open Access


    An Optimized Neural Network with Bat Algorithm for DNA Sequence Classification

    Muhammad Zubair Rehman1, Muhammad Aamir2,*, Nazri Mohd. Nawi3, Abdullah Khan4, Saima Anwar Lashari5, Siyab Khan4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 493-511, 2022, DOI:10.32604/cmc.2022.021787


    Recently, many researchers have used nature inspired metaheuristic algorithms due to their ability to perform optimally on complex problems. To solve problems in a simple way, in the recent era bat algorithm has become famous due to its high tendency towards convergence to the global optimum most of the time. But, still the standard bat with random walk has a problem of getting stuck in local minima. In order to solve this problem, this research proposed bat algorithm with levy flight random walk. Then, the proposed Bat with Levy flight algorithm is further hybridized with three different variants of ANN.… More >

  • Open Access


    Compact Bat Algorithm with Deep Learning Model for Biomedical EEG EyeState Classification

    Souad Larabi-Marie-Sainte1, Eatedal Alabdulkreem2, Mohammad Alamgeer3, Mohamed K Nour4, Anwer Mustafa Hilal5,*, Mesfer Al Duhayyim6, Abdelwahed Motwakel5, Ishfaq Yaseen5

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4589-4601, 2022, DOI:10.32604/cmc.2022.027922

    Abstract Electroencephalography (EEG) eye state classification becomes an essential tool to identify the cognitive state of humans. It can be used in several fields such as motor imagery recognition, drug effect detection, emotion categorization, seizure detection, etc. With the latest advances in deep learning (DL) models, it is possible to design an accurate and prompt EEG EyeState classification problem. In this view, this study presents a novel compact bat algorithm with deep learning model for biomedical EEG EyeState classification (CBADL-BEESC) model. The major intention of the CBADL-BEESC technique aims to categorize the presence of EEG EyeState. The CBADL-BEESC model performs feature… More >

  • Open Access


    Extreme Learning Bat Algorithm in Brain Tumor Classification

    G. R. Sreekanth1, Adel Fahad Alrasheedi2, K. Venkatachalam3, Mohamed Abouhawwash4,5,*, S. S. Askar2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 249-265, 2022, DOI:10.32604/iasc.2022.024538

    Abstract Brain tumor is considered as an unusual cell that presents and grows in the brain. Similarly, it may lead to cancerous or non-cancerous. So, to improve the survival rate of the patient and to give the best treatment at the earliest, it’s very necessary for early prediction of tumor. Accurate classification of tumor in the brain is important for improving the diagnosis. In accordance with that, various research programs are invited for the better treatment of the patients. Machine Learning (ML) algorithms are applied to help the health associates for the classification of brain tumor and present their diagnosis. This… More >

  • Open Access


    Bat-Inspired Optimization for Intrusion Detection Using an Ensemble Forecasting Method

    R. Anand Babu1,*, S. Kannan2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 307-323, 2022, DOI:10.32604/iasc.2022.024098

    Abstract An Intrusion detection system (IDS) is extensively used to identify cyber-attacks preferably in real-time and to achieve integrity, confidentiality, and availability of sensitive information. In this work, we develop a novel IDS using machine learning techniques to increase the performance of the attack detection process. In order to cope with high dimensional feature-rich traffic in large networks, we introduce a Bat-Inspired Optimization and Correlation-based Feature Selection (BIOCFS) algorithm and an ensemble classification approach. The BIOCFS is introduced to estimate the correlation of the identified features and to choose the ideal subset for training and testing phases. The Ensemble Classifier (EC)… More >

  • Open Access


    Modified Bat Algorithm for Optimal VM's in Cloud Computing

    Amit Sundas1, Sumit Badotra1,*, Youseef Alotaibi2, Saleh Alghamdi3, Osamah Ibrahim Khalaf4

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2877-2894, 2022, DOI:10.32604/cmc.2022.025658

    Abstract All task scheduling applications need to ensure that resources are optimally used, performance is enhanced, and costs are minimized. The purpose of this paper is to discuss how to Fitness Calculate Values (FCVs) to provide application software with a reliable solution during the initial stages of load balancing. The cloud computing environment is the subject of this study. It consists of both physical and logical components (most notably cloud infrastructure and cloud storage) (in particular cloud services and cloud platforms). This intricate structure is interconnected to provide services to users and improve the overall system's performance. This case study is… More >

  • Open Access


    Echo Location Based Bat Algorithm for Energy Efficient WSN Routing

    Anwer Mustafa Hilal1,*, Siwar Ben Haj Hassine2, Jaber S. Alzahrani3, Masoud Alajmi4, Fahd N. Al-Wesabi2,5, Mesfer Al Duhayyim6, Ishfaq Yaseen1, Abdelwahed Motwakel1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6351-6364, 2022, DOI:10.32604/cmc.2022.024489

    Abstract Due to the wide range of applications, Wireless Sensor Networks (WSN) are increased in day to day life and becomes popular. WSN has marked its importance in both practical and research domains. Energy is the most significant resource, the important challenge in WSN is to extend its lifetime. The energy reduction is a key to extend the network's lifetime. Clustering of sensor nodes is one of the well-known and proved methods for achieving scalable and energy conserving WSN. In this paper, an energy efficient protocol is proposed using metaheuristic Echo location-based BAT algorithm (ECHO-BAT). ECHO-BAT works in two stages. First… More >

  • Open Access


    Optimizing Steering Angle Predictive Convolutional Neural Network for Autonomous Car

    Hajira Saleem1, Faisal Riaz1, Asadullah Shaikh2, Khairan Rajab2,3, Adel Rajab2,*, Muhammad Akram2, Mana Saleh Al Reshan2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2285-2302, 2022, DOI:10.32604/cmc.2022.022726

    Abstract Deep learning techniques, particularly convolutional neural networks (CNNs), have exhibited remarkable performance in solving vision-related problems, especially in unpredictable, dynamic, and challenging environments. In autonomous vehicles, imitation-learning-based steering angle prediction is viable due to the visual imagery comprehension of CNNs. In this regard, globally, researchers are currently focusing on the architectural design and optimization of the hyperparameters of CNNs to achieve the best results. Literature has proven the superiority of metaheuristic algorithms over the manual-tuning of CNNs. However, to the best of our knowledge, these techniques are yet to be applied to address the problem of imitation-learning-based steering angle prediction.… More >

  • Open Access


    New Modified Controlled Bat Algorithm for Numerical Optimization Problem

    Waqas Haider Bangyal1, Abdul Hameed1, Jamil Ahmad2, Kashif Nisar3,*, Muhammad Reazul Haque4, Ag. Asri Ag. Ibrahim3, Joel J. P. C. Rodrigues5,6, M. Adil Khan7, Danda B. Rawat8, Richard Etengu4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2241-2259, 2022, DOI:10.32604/cmc.2022.017789

    Abstract Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been examined for fifteen well-known benchmark… More >

  • Open Access


    Multi-Objective Adapted Binary Bat for Test Suite Reduction

    Nagwa Reda1, Abeer Hamdy2,*, Essam A. Rashed1,3

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 781-797, 2022, DOI:10.32604/iasc.2022.019669

    Abstract Regression testing is an essential quality test technique during the maintenance phase of the software. It is executed to ensure the validity of the software after any modification. As software evolves, the test suite expands and may become too large to be executed entirely within a limited testing budget and/or time. So, to reduce the cost of regression testing, it is mandatory to reduce the size of the test suite by discarding the redundant test cases and selecting the most representative ones that do not compromise the effectiveness of the test suite in terms of some predefined criteria such as… More >

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