All task scheduling applications need to ensure that resources are optimally used,performance is enhanced,and costs are *** purpose of this paper is to discuss how to Fitness Calculate Values(FCVs)to provide applicati...
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All task scheduling applications need to ensure that resources are optimally used,performance is enhanced,and costs are *** 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 *** cloud computing environment is the subject of this *** 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 *** case study is one of the most important segments of cloud computing,i.e.,Load *** paper aims to introduce a new approach to balance the load among Virtual Machines(VM’s)of the cloud computing *** proposed method led to the proposal and implementation of an algorithm inspired by the batalgorithm(BA).This proposed modified bat algorithm(MBA)allows balancing the load among virtual *** proposed algorithm works in two variants:MBA with Overloaded Optimal Virtual Machine(MBAOOVM)and modified bat algorithm with Balanced Virtual Machine(MBABVM).MBA generates cost-effective solutions and the strengths of MBA are finally validated by comparing it with batalgorithm.
Metaheuristic algorithms due to flexibility can be applied to a wide range of complex engineering optimization problems. The effectiveness, efficiency, and adaptability of such algorithms can significantly be enhanced...
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Metaheuristic algorithms due to flexibility can be applied to a wide range of complex engineering optimization problems. The effectiveness, efficiency, and adaptability of such algorithms can significantly be enhanced through the modified variants. In this paper a novel modified bat algorithm (MoBA) using the concept of expectation value is proposed and evaluated using different benchmark functions, and then compared and ranked among other previously improved variants. Subsequently, the proposed MoBA was hybridized with a pretrained multitask adaptive deep learning model to generate 3D spatial subsurface mapping of geothermal temperatures in Catalonia, Spain. The success, effectiveness and superiority of the presented MoBA in compare with previously modified firefly algorithm was confirmed using different accuracy performance criteria by at least 1.71% improvement.
System-on-Chip (SoC) is a structure in which semiconductor components are integrated into a single die. As a result, testing time should be reduced to achieve a low cost for each chip. Effective test scheduling can re...
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System-on-Chip (SoC) is a structure in which semiconductor components are integrated into a single die. As a result, testing time should be reduced to achieve a low cost for each chip. Effective test scheduling can reduce the SoC testing time, which is more challenging due to its complexity. In this paper, the modified bat algorithm-based test scheduling is proposed. Testing is carried out on the SoC ITC'02 benchmark circuits. The modifiedbat method is a recently heuristic algorithm that performs global optimization by imitating bat echolocation. Compared to other state-of-the-art algorithms, the modifiedbat Optimization method reduces testing time on SoCs. This paper improves the algorithm's exploration process by adjusting the equation for bat loudness (A(0)) and pulse emission rate (r). The modified bat algorithm converges to the optimal solution faster. It has been used in 14 international standard test functions. The test results indicate that the modified bat algorithm has a fast convergence speed, which minimizes the testing time compared to other evolutionary algorithms on the ITC'02 SoC benchmark circuits.
Grid-connected photovoltaic (PV) systems play an important role in reducing emissions resulting from conventional fossil-fuel-based power plants. However, in order to effectively integrated PV systems into the power s...
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Grid-connected photovoltaic (PV) systems play an important role in reducing emissions resulting from conventional fossil-fuel-based power plants. However, in order to effectively integrated PV systems into the power system, many challenges regarding these renewable resources such as extracting maximum power under various conditions should be solved. This paper suggests an enhanced maximum power point tracking (MPPT) by the fuzzy logic controller (FLC) and a modified bat algorithm (MBA) to fine-tune the parameters of the controller. The FLC is greatly affected by rule base and membership functions (MFs). The fine-tuning of such parameters cannot be appropriate when accurate information regarding the system is not available. To overcome the above-mentioned challenges, the MBA algorithm is utilized to optimize the scaling factors of MFs. Simulation results confirm that the suggested MBA-FLC method can effectively cope with the global maxima under different weather circumstances with high efficiency, faster tracking and stable output.
Multistage characteristic has become one of the essential issues of batch process and several stage division approaches have been introduced to monitor the process. As the non-Gaussian and nonlinear problems of batch ...
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Multistage characteristic has become one of the essential issues of batch process and several stage division approaches have been introduced to monitor the process. As the non-Gaussian and nonlinear problems of batch process, a hybrid intelligent method is developed to monitor the multistage conditions in this paper. The proposed algorithm includes converged stage division (CSD), multi-boundary hypersphere support vector data description (MH-SVDD), and modified bat algorithm (MBA). CSD algorithm is utilized to process the data and make the stage division, which consists of data length processing, three-dimension unfolding, and K-means clustering. MH-SVDD algorithm is to construct two hyperspheres, which can overcome the deficiency of traditional boundary SVDD. The Gaussian kernel function width parameter of MH-SVDD plays a very significant role in multistage fault monitoring, a modified bat algorithm is established to select the optimal parameter. The experimental of the semiconductor etching process is described, and the results demonstrate that the proposed model can gain higher fault monitoring accuracy in multistage condition monitoring of the batch process.
This paper deals with an extensive variant of the inverse p-facility maxian location problem on networks in which the set of vertices is considered as the existing client points and the aim is to modify (augment or re...
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This paper deals with an extensive variant of the inverse p-facility maxian location problem on networks in which the set of vertices is considered as the existing client points and the aim is to modify (augment or reduce) the underlying vertex weights and the arc lengths at the minimum overall cost with respect to the modification bounds so that a given set of p vertices, denoting the predetermined facility sites, becomes a p-facility maxian location of the perturbed network. A novel modified directional batalgorithm, as a meta-heuristic approach, is developed to solve the problem under the bottleneck-type Hamming, sum-type Hamming, rectilinear and Chebyshev cost norms. Through computational tests, the effectiveness of the proposed algorithm is shown.
Nowadays, renewable energy sources based distributed generations (REDGs) interconnection with distribution system is gaining more attention by the power system engineers since it meets increasing load demand and cance...
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Nowadays, renewable energy sources based distributed generations (REDGs) interconnection with distribution system is gaining more attention by the power system engineers since it meets increasing load demand and cancel out environmental threats. Suitable incorporation of REDGs in radial distribution system (RDS) is vital in ensuring qualitative network operational profits. In this present approach a modified bat algorithm (MBA) based optimization method is employed to allocate solar and wind DGs along with DSTATCOM in RDS. The proposed new multi objective function to mitigate power loss, bus voltage development stability betterment and Total Operating Cost (TOC) minimization. Proper modelling of solar irradiance and wind speed have been done in the RDS. The present approach is tested to Indian countrified system structure and standard IEEE 69-bus system, and received satisfactory outputs.
In this paper, an optimal design of the two-degree-of-freedom proportional-integral-derivative-accelerated (2DOF-PIDA) controllers for the liquid-level system based on the modern optimization by using the modifiedbat...
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In this paper, an optimal design of the two-degree-of-freedom proportional-integral-derivative-accelerated (2DOF-PIDA) controllers for the liquid-level system based on the modern optimization by using the modified bat algorithm (MBA) is proposed. The MBA is the new modified version of the original batalgorithm (BA) developed from the echolocation behaviour of micro bats. To improve its exploration and exploitation properties, the random number drawn from a Levy-flight distribution and new loudness and pulse emission rate functions are proposed. Performance of the MBA over the BA investigated against 10 benchmark functions is presented in this paper. Results of the 2DOF-PIDA controllers designed by the proposed MBA for the liquid-level system are compared with those of the one-degree-of-freedom proportional-integral-derivative (1DOF-PID) controller designed by Ziegler-Nichols (ZN) tuning rule, 2DOF-PID designed by Araki-Taguchi (AT) tuning rule and 1DOF-PID and 1DOF-PIDA controllers designed by the MBA. As results, it was found that the liquid-level controlled system with the 2DOF-PIDA controllers designed by the MBA can provide very satisfactory responses superior to that with the 2DOF-PID controllers designed by AT and MBA and 1DOF-PID controller designed by ZN, significantly.
With the arrival of big data, data mining analysis and high-performance forecasting of wind speed is increasingly attracting close attention. Despite the fact that massive investigations concerning wind speed forecast...
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With the arrival of big data, data mining analysis and high-performance forecasting of wind speed is increasingly attracting close attention. Despite the fact that massive investigations concerning wind speed forecasting in theory and practice have been conducted by multiple researchers, studies concerning multi-step-ahead forecasting are still lacking, impeding the further development in the field. In this study, a novel hybrid approach is proposed for multi-step-ahead wind speed forecasting utilizing optimal feature selection and an artificial neural network optimized by a modified bat algorithm with cognition strategy. The proposed hybrid model can largely remedy the deficiencies of neural networks for multi-step-ahead forecasting, which is validated for different forecasting horizons, and is shown to work effectively. Finally, experiments based on three verification units from the city of Penglai in China are conducted effectively, illustrating that the proposed model not only has advantages when compared with benchmark models, but also has great potential for application to wind power system. (C) 2017 Elsevier Ltd. All rights reserved.
The paper proposes a new modified bat algorithm (MBA) for solving combined economic and emission load dispatch (CEED) problems where transmission power losses are considered. The MBA is first developed in the paper by...
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ISBN:
(纸本)9783319509044;9783319509037
The paper proposes a new modified bat algorithm (MBA) for solving combined economic and emission load dispatch (CEED) problems where transmission power losses are considered. The MBA is first developed in the paper by modifying the several modifications on the conventional batalgorithm (BA) in aim to improve the performance of the BA. The MBA is tested on two different systems with the transmission power losses. The performance of the MBA is evaluated by comparing obtained results with BA and other existing algorithms available in the study. As a result, it can be concluded that the MBA outperforms the BA and is very strong for solving the CEED problem.
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