Dark images can be enhanced in a controlled manner with the help of nature inspired metaheuristic algorithm. In this case image enhancement has been taken as a nonlinear optimization problem. bat algorithm (BA) and Cu...
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ISBN:
(纸本)9788132222507;9788132222491
Dark images can be enhanced in a controlled manner with the help of nature inspired metaheuristic algorithm. In this case image enhancement has been taken as a nonlinear optimization problem. bat algorithm (BA) and Cuckoo Search (CS) algorithm is one of the most powerful metaheuristic algorithms. In this paper these two algorithms have been modified by chaotic sequence and levy flight. In BA levy flight with chaotic step size helps to do intensification. In CS algorithm the random walk has been done via chaotic sequence. Entropy and edge information has been used as objective function. From quantitative and visual analysis it is clear that chaotic levy BA outperforms the chaotic CS algorithm.
bat algorithm is a recent addition to the bio-inspired algorithms, considered as a new metaheuristic algorithm based on bat behaviour. This work presents, the optimal solution of economic load dispatch (ELD) is obtain...
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ISBN:
(纸本)9781467361507;9781467361491
bat algorithm is a recent addition to the bio-inspired algorithms, considered as a new metaheuristic algorithm based on bat behaviour. This work presents, the optimal solution of economic load dispatch (ELD) is obtained using the proposed bat algorithm. Here the operating cost of a thermal power plant is optimized using bat algorithm. Numerical results show that the proposed method has good convergence property and better in quality of solution than PSO and IWD reported in recent literature. The main advantage of the proposed technique is easy is implement and capable of finding feasible near global optimal solution with less computational effort. bat algorithm is easy to implement and priory in terms of accuracy and efficiency compared to other algorithms. In order to illustrate the effectiveness of the proposed method, it has been tested on 3 and 6-unit system.
This article is expanded the technique for clustering the images from Convolutional Neural Network (CNN) with bat algorithm (BA). Varian images extract the features from CNN for identifting each image data. BA categor...
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ISBN:
(数字)9781665485593
ISBN:
(纸本)9781665485593
This article is expanded the technique for clustering the images from Convolutional Neural Network (CNN) with bat algorithm (BA). Varian images extract the features from CNN for identifting each image data. BA categorize those image data for improved clustering, assist with fuzzy logic systems. Computational result are comparative experiment results between CNN and Fuzzy BA, mean squared error and root mean squared error respectively.
In this paper, an improved kernel independent component analysis (KICA) algorithm is proposed for multi-user detection (MUD). In this algorithm, a new hybrid kernel function is adopted. In addition, the bat algorithm ...
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ISBN:
(纸本)9783037857519
In this paper, an improved kernel independent component analysis (KICA) algorithm is proposed for multi-user detection (MUD). In this algorithm, a new hybrid kernel function is adopted. In addition, the bat algorithm is applied to the optimizing process of independent component separation. Simulation results show that the new hybrid kernel function performs better in MUD than other kernel functions,and the improved KICA with bat algorithm has the smallest bit error rate(BER) when compared with classical FastICA and KICA algorithms.
bat algorithm (BA) is newly proposed bio-inspired metaheuristic algorithm with the inspiration of the echolocation of bats in nature. Several experimental results have proven to the effectiveness and performance of BA...
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ISBN:
(纸本)9781509006229
bat algorithm (BA) is newly proposed bio-inspired metaheuristic algorithm with the inspiration of the echolocation of bats in nature. Several experimental results have proven to the effectiveness and performance of BA. However, BA may fail to find the global optimal solution occasionally. In this paper, a kind of classical search technology, called variable neighborhood search (VNS), is incorporated into BA as a local search tool. An improved version of BA namely variable neighborhood bat algorithm (VNBA), is thus proposed. In VNBA, the classic BA as a global search tool searches the whole space globally, and this can significantly shrink the search space. Subsequently, VNS as a local search tool is implemented to find the final best solution within the small promising area. After that, the VNBA is benchmarked by sixteen standard benchmark functions. The experimental results imply that VNBA takes the absolute advantage over the basic BA.
The use of meta -heuristic algorithms for solving real world problems increases day by day. bat algorithm is a meta heuristic optimization algorithm based on the echolocation behavior of microbats. bat algorithm has a...
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ISBN:
(纸本)9781467387897
The use of meta -heuristic algorithms for solving real world problems increases day by day. bat algorithm is a meta heuristic optimization algorithm based on the echolocation behavior of microbats. bat algorithm has advantage which claimed to provide very quick convergence at a very initial stage by automatic switching from exploration to exploitation. Hereby, algorithm loses exploration capability highly at the following iterations, and it may lead to premature convergence. To cope with this deficiency, this paper proposes a novel version of bat algorithm based on instantaneous exploitation feature. Conducted experiments on ten well-known benchmark test functions have shown that the proposed Instantaneous Exploitation Based bat algorithm can outperform the standard bat algorithm.
Optimization is defined as finding the alternate solutions to a problem, tinder the given constraints. Maximizing the performance level is one of the objectives of optimization, which can be achieved by satisfying des...
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ISBN:
(纸本)9789380544199
Optimization is defined as finding the alternate solutions to a problem, tinder the given constraints. Maximizing the performance level is one of the objectives of optimization, which can be achieved by satisfying desirable factors and minimizing the undesirable ones. When a problem cannot be solved in polynomial time or consumes long time to solve, then alternative solutions of the problem will be explored and near optimal solution is accepted. To tackle these napes of problems, one of the three approaches are used: Heuristics, Meta-Heuristics and Hyper-Heuristics. bat algorithm is one of the meta-heuristic algorithms, which optimizes the solution using echolocation and applicable in solving various combinatorial problems. In this research work, analysis of various bat variants is done and further research areas are explored, in the field of meta heuristic approaches.
Multitasking optimization is an emerging research field which has attracted lot of attention in the scientific community. The main purpose of this paradigm is how to solve multiple optimization problems or tasks simul...
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ISBN:
(纸本)9783030867973;9783030504250
Multitasking optimization is an emerging research field which has attracted lot of attention in the scientific community. The main purpose of this paradigm is how to solve multiple optimization problems or tasks simultaneously by conducting a single search process. The main catalyst for reaching this objective is to exploit possible synergies and complementarities among the tasks to be optimized, helping each other by virtue of the transfer of knowledge among them (thereby being referred to as Transfer Optimization). In this context, Evolutionary Multitasking addresses Transfer Optimization problems by resorting to concepts from Evolutionary Computation for simultaneous solving the tasks at hand. This work contributes to this trend by proposing a novel algorithmic scheme for dealing with multitasking environments. The proposed approach, coined as Coevolutionary bat algorithm, finds its inspiration in concepts from both co-evolutionary strategies and the metaheuristic bat algorithm. We compare the performance of our proposed method with that of its Multifactorial Evolutionary algorithm counterpart over 15 different multitasking setups, composed by eight reference instances of the discrete Traveling Salesman Problem. The experimentation and results stemming therefrom support the main hypothesis of this study: the proposed Coevolutionary bat algorithm is a promising meta-heuristic for solving Evolutionary Multitasking scenarios.
Due to the effect of a quantization error, it is not possible to fully restore the original image in the lossy wavelet-based image compression. However, the quantization error can be minimized by optimizing or evolvin...
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ISBN:
(纸本)9781728172231
Due to the effect of a quantization error, it is not possible to fully restore the original image in the lossy wavelet-based image compression. However, the quantization error can be minimized by optimizing or evolving the filter bank. In this work, the coefficients of the standard wavelet filter and its inverse filter were optimized by evolution of bat algorithm. The optimized wavelet filters were used with the SPIHT encoder/decoder for image compression. The performance of the optimized filters in reconstruction during the decompression process was investigated using the metrics PSNR, MSE and SSIM. The results obtained show that the proposed filter outperforms standard wavelet filters by minimizing the error between the original and the decompressed image.
In this paper, Power System Stabilizer (PSS) based on hybrid Sliding Mode Controller (SMC) and fractional order PID controller ((PID mu)-D-lambda) is proposed for optimal control of power system, using a new metaheuri...
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ISBN:
(纸本)9781479989478
In this paper, Power System Stabilizer (PSS) based on hybrid Sliding Mode Controller (SMC) and fractional order PID controller ((PID mu)-D-lambda) is proposed for optimal control of power system, using a new metaheuristic optimization bat algorithm (BA) inspired by the echolocation behavior to improve power system stability. The aim of this study is to find robust controller for demonstrating the availability of the proposed controller, and to achieve best desired output. Here, we have chosen SMC as one of the most effective control methodologies for adjusting the states of the system to their preferred values to supply the excellent damping under severe disturbances. The problem of SMC-FOPID design is transformed to an optimization problem based on performance index, which is Integral of the Time Weighted Absolute Error (ITAE). Where, BA has been employed to adjust the optimal controller parameters. The effectiveness of SMC-FOPID has been tested on a Single Machine Infinite Bus (SMIB) power system under different cases, including operating. The performance of SMC-FOPID controller in power system is compared with a conventional PSS. The simulation results greatly indicate the validity and effectiveness of the proposed controller, and superior robust performance for improvement power system stability compared with the PSS controller for each case.
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