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Search Results (106)
  • Open Access

    ARTICLE

    Transient Simulation and Optimization of Regional Integrated Energy System

    Xueqin Tian1, Mengran Cui2, Tong Xu1, Jinfei Sun2, Xinlei Wang1, Jiangxiang Guo2, De-Gejirifu1,*, Na Wang1

    Energy Engineering, Vol.119, No.3, pp. 1031-1045, 2022, DOI:10.32604/ee.2022.015984

    Abstract A modeling method of regional integrated energy system based on bus method and transient simulation is proposed, and the system optimization is based on the dynamic balance of supply and demand in the whole year energy supply cycle. A CCHP system of gas turbine coupled with ground source heat pump and electric refrigeration unit is constructed. The energy relationship of the system is described by bus structure, and the transient calculation model is built on TRNSYS platform. The weighted sum of annual total cost saving rate, primary energy saving rate and environmental pollutant shadow cost saving rate is taken as… More >

  • Open Access

    ARTICLE

    Design of Energy Efficient WSN Using a Noble SMOWA Algorithm

    Avishek Banerjee1, Deepak Garg1, Victor Das2, Laxminarayan Sahoo3, Ira Nath4, Vijayakumar Varadarajan5, Ketan Kotecha6,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3585-3600, 2022, DOI:10.32604/cmc.2022.025233

    Abstract In this paper, the establishment of efficient Wireless Sensor Network (WSN) networks has been projected to minimize the consumption of energy using a new Self-adaptive Multi-Objective Weighted Approach (SMOWA) algorithm for solving a multi-objective problem. The Different WSN nodes deployment policies have been proposed and applied in this paper to design an efficient Wireless Sensor Network to minimize energy consumption. After that, the cluster head for each cluster has been selected with the help of the duty cycle. After configuring the WSN networks, the SMOWA algorithms have been developed to obtain the minimum energy consumption for the networks. Energy minimization,… More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization of Energy Aware Virtual Machine Placement in Cloud Data Center

    B. Gomathi1, B. Saravana Balaji2, V. Krishna Kumar3, Mohamed Abouhawwash4,5,*, Sultan Aljahdali6, Mehedi Masud6, Nina Kuchuk7

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1771-1785, 2022, DOI:10.32604/iasc.2022.024052

    Abstract Cloud computing enables cloud providers to outsource their Information Technology (IT) services from data centers in a pay-as-you-go model. However, Cloud infrastructure comprises virtualized physical resources that consume huge amount of energy and emits carbon footprints to environment. Hence, there should be focus on optimal assignment of Virtual Machines (VM) to Physical Machines (PM) to ensure the energy efficiency and service level performance. In this paper, The Pareto based Multi-Objective Particle Swarm Optimization with Composite Mutation (PSOCM) technique has been proposed to improve the energy efficiency and minimize the Service Level Agreement (SLA) violation in Cloud Environment. In this paper,… More >

  • Open Access

    ARTICLE

    Time-Variant Reliability-Based Multi-Objective Fuzzy Design Optimization for Anti-Roll Torsion Bar of EMU

    Pengpeng Zhi1,2,3, Zhonglai Wang1,2,*, Bingzhi Chen3, Ziqiang Sheng4

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1001-1022, 2022, DOI:10.32604/cmes.2022.019835

    Abstract Although various types of anti-roll torsion bars have been developed to inhibit excessive roll angle of the electric multiple unit (EMU) car body, it is critical to ensure the reliability of structural design due to the complexity of the problems involving time and uncertainties. To address this issue, a multi-objective fuzzy design optimization model is constructed considering time-variant stiffness and strength reliability constraints for the anti-roll torsion bar. A hybrid optimization strategy combining the design of experiment (DoE) sampling and non-linear programming by quadratic lagrangian (NLPQL) is presented to deal with the design optimization model. To characterize the effect of… More >

  • Open Access

    ARTICLE

    Crashworthiness Design and Multi-Objective Optimization for Bio-Inspired Hierarchical Thin-Walled Structures

    Shaoqiang Xu1, Weiwei Li1,*, Lin Li2, Tao Li1, Chicheng Ma1

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 929-947, 2022, DOI:10.32604/cmes.2022.018964

    Abstract Thin-walled structures have been used in many fields due to their superior mechanical properties. In this paper, two types of hierarchical multi-cell tubes, inspired by the self-similarity of Pinus sylvestris, are proposed to enhance structural energy absorption performance. The finite element models of the hierarchical structures are established to validate the crashworthiness performance under axial dynamic load. The theoretical model of the mean crushing force is also derived based on the simplified super folded element theory. The finite element results demonstrate that the energy absorption characteristics and deformation mode of the bionic hierarchical thin-walled tubes are further improved with the… More >

  • Open Access

    ARTICLE

    An Adaptive Classifier Based Approach for Crowd Anomaly Detection

    Sofia Nishath, P. S. Nithya Darisini*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 349-364, 2022, DOI:10.32604/cmc.2022.023935

    Abstract Crowd Anomaly Detection has become a challenge in intelligent video surveillance system and security. Intelligent video surveillance systems make extensive use of data mining, machine learning and deep learning methods. In this paper a novel approach is proposed to identify abnormal occurrences in crowded situations using deep learning. In this approach, Adaptive GoogleNet Neural Network Classifier with Multi-Objective Whale Optimization Algorithm are applied to predict the abnormal video frames in the crowded scenes. We use multiple instance learning (MIL) to dynamically develop a deep anomalous ranking framework. This technique predicts higher anomalous values for abnormal video frames by treating regular… More >

  • Open Access

    ARTICLE

    Smart Anti-Pinch Window Simulation Using H-/H Criterion and MOPSO

    Maedeh Mohammadi Azni1, Mohammad Ali Sadrnia1, Shahab S. Band2,*, Zulkefli Bin Mansor3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 215-226, 2022, DOI:10.32604/cmc.2022.023030

    Abstract Automobile power windows are mechanisms that can be opened and shut with the press of a button. Although these windows can comfort the effort of occupancy to move the window, failure to recognize the person's body part at the right time will result in damage and in some cases, loss of that part. An anti-pinch mechanism is an excellent choice to solve this problem, which detects the obstacle in the glass path immediately and moves it down. In this paper, an optimal solution is presented for fault detection of the anti-pinch window system. The anti-pinch makes it possible to detect… More >

  • Open Access

    ARTICLE

    Weighted-adaptive Inertia Strategy for Multi-objective Scheduling in Multi-clouds

    Mazen Farid1,3,*, Rohaya Latip1,2, Masnida Hussin1, Nor Asilah Wati Abdul Hamid1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1529-1560, 2022, DOI:10.32604/cmc.2022.021410

    Abstract One of the fundamental problems associated with scheduling workflows on virtual machines in a multi-cloud environment is how to find a near-optimum permutation. The workflow scheduling involves assigning independent computational jobs with conflicting objectives to a set of virtual machines. Most optimization methods for solving non-deterministic polynomial-time hardness (NP-hard) problems deploy multi-objective algorithms. As such, Pareto dominance is one of the most efficient criteria for determining the best solutions within the Pareto front. However, the main drawback of this method is that it requires a reasonably long time to provide an optimum solution. In this paper, a new multi-objective minimum… More >

  • Open Access

    ARTICLE

    Cat-Inspired Deep Convolutional Neural Network for Bone Marrow Cancer Cells Detection

    R. Kavitha1,*, N. Viswanathan2

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1305-1320, 2022, DOI:10.32604/iasc.2022.022816

    Abstract Bone marrow cancer is considered to be the most complex and dangerous disease which results due to an uncontrolled growth of white blood cells called leukocytes. Acute Lymphoblastic Leukemia (ALL) and Multiple Myeloma (MM) are considered to be important categories of bone cancers, which induces a larger number of cancer cells in the bone marrow, results in preventing the production of healthy blood cells. The advent of Artificial Intelligence, especially machine and deep learning, has expanded humanity’s capacity to analyze and detect these increasingly complex diseases. But, accurate detection of cancer cells and reducing the probability of false alarm rates… More >

  • Open Access

    ARTICLE

    Multi-Objective Modified Particle Swarm Optimization for Test Suite Reduction (MOMPSO)

    U. Geetha1,*, Sharmila Sankar2

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 899-917, 2022, DOI:10.32604/csse.2022.022621

    Abstract Software testing plays a pivotal role in entire software development lifecycle. It provides researchers with extensive opportunities to develop novel methods for the optimized and cost-effective test suite Although implementation of such a cost-effective test suite with regression testing is being under exploration still it contains lot of challenges and flaws while incorporating with any of the new regression testing algorithm due to irrelevant test cases in the test suite which are not required. These kinds of irrelevant test cases might create certain challenges such as code-coverage in the test suite, fault-tolerance, defects due to uncovered-statements and overall-performance at the… More >

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