ABSTRACTThis paper presents an optimization-driven classifier for classifying the brain tumour considering MRI. Here, the pre-operative and post-operative MRI is subjected to pre-processing, which is performed using f...
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ABSTRACTThis paper presents an optimization-driven classifier for classifying the brain tumour considering MRI. Here, the pre-operative and post-operative MRI is subjected to pre-processing, which is performed using filtering and Region of Interest (RoI) extraction techniques. The pre-processed output is fed to segmentation wherein the U-Net model is adapted for generating the segments. Then, the extraction of histogram features is done and the classification of tumours is done by U-Net, which is trained using the proposed Poor birdswarm Optimization algorithm (PRBSA). Here, PRBSA is the integration of the Poor and rich optimization (PRO) algorithm and bird swarm algorithm (BSA). At last, the classified output is considered for pixel change detection, which is carried out using speeded-up robust features (SURF). The proposed PRBSA-based U-Net offered improved performance with the highest accuracy of 94%, highest sensitivity of 93.7%, and highest specificity of 94%.
Wide-area damping control is one of the most used methods for improving stability in power systems. However, this type of control requires suitably tuning the main controller and wide-area controller under dependency ...
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Wide-area damping control is one of the most used methods for improving stability in power systems. However, this type of control requires suitably tuning the main controller and wide-area controller under dependency and constrains. In this paper, we propose a method for wide-area optimal damping control based on the integral of the time-weighted absolute error (ITAE) to mitigate low-frequency oscillations in the interconnected power grid. First, we perform the modal analysis of the open-loop system to determine the weak damping-interval oscillation mode. Then, based on the geometric observability and controllability indices, we derive the wide-area optimal closed-loop control. Finally, we formulate an objective function using the ITAE and employ the bird swarm algorithm to optimize the structurally constrained controller parameters for the coordination control. Simulation results demonstrate that the proposed control strategy has a highly accurate dynamic response and effectively suppresses inter-area oscillations in the interconnected power systems.
Particle filter(PF) can solve the problem of state estimation under strong non-linear non-Gaussian noise condition with respect to traditional Kalman filter(KF) and those improved KFs such as extended KF(EKF) and unsc...
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Particle filter(PF) can solve the problem of state estimation under strong non-linear non-Gaussian noise condition with respect to traditional Kalman filter(KF) and those improved KFs such as extended KF(EKF) and unscented KF(UKF). However, problems such as particle depletion and particle degradation affect the performance of PF. Optimizing the particle set to high likelihood region with intelligent optimization algorithm results in a more reasonable distribution of the sampling particles and more accurate state estimation. In this paper, a novel bird swarm algorithm based PF(BSAPF) is presented. Firstly, different behavior models are established by emulating the predation, flight, vigilance and follower behavior of the birds. Then, the observation information is introduced into the optimization process of the proposal distribution with the design of fitness function. In order to prevent particles from getting premature(being stuck into local optimum) and increase the diversity of particles, Lévy flight is designed to increase the randomness of particle's movement. Finally,the proposed algorithm is applied to estimate the speed of the train under the condition that the measurement noise of the wheel sensor is non-Gaussian distribution. Simulation study and experimental results both show that BSAPF is more accurate and has more effective particle number as compared with PF and UKF, demonstrating the promising performance of the method.
In this paper, single-machine scheduling with carbon emission index is studied. The objective function is to minimize the sum of total flow time and carbon emission. Firstly, the problem is shown to be NP-hard by Turi...
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ISBN:
(纸本)9783319959290;9783319959306
In this paper, single-machine scheduling with carbon emission index is studied. The objective function is to minimize the sum of total flow time and carbon emission. Firstly, the problem is shown to be NP-hard by Turing reduction. Then mathematical programming (MP) model is established. A pseudo-time algorithm based on dynamic programming (DPA) is proposed for small scale. And a bird swarm algorithm (BSA) is proposed to compete with DPA. In addition, simulation experiments are used to compare the proposed algorithms. DPA is shown to be more efficient for small scale problem, and BSA is better for large scale problem.
Most researches on process planning optimized machining process routings and cutting parameters independently and ignored their comprehensive effects on carbon reduction. In order to further reduce carbon emissions in...
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ISBN:
(纸本)9780791851357
Most researches on process planning optimized machining process routings and cutting parameters independently and ignored their comprehensive effects on carbon reduction. In order to further reduce carbon emissions in manufacturing processes, an optimization model of cutting parameters and machining process routings is proposed to minimize total carbon emissions and total processing time of all processes. Carbon emissions include those caused by energy consumptions of machines in cutting state, material consumption of cutting tools and cutting fluid in all processes. As the optimization of cutting parameters is a continuous optimization problem, but the optimization of machining process routings including machining methods, process sequences, machine allocating and cutter selecting are discrete optimization problems, the whole optimization of process planning is divided into two parts. One is continuous optimization of cutting parameters. Another is discrete optimization of machining process routings. A hybrid optimization strategy of bird swarm algorithm (BSA) and NSGA- II algorithm is proposed to optimize the proposed model. Cutting parameters are optimized using BSA aiming at minimizing carbon emissions and machining time of each process. Machining process routings are optimized using NSGA- II under each optimized group of cutting parameters from the Pareto set. Four kinds of mutation operators in NSGA- II are designed for the discrete optimization of machining process routings. A workpiece with six machining features to be machined in a workshop with two CNC lathes, two CNC milling machines and two drilling machines is taken as a case study. The validity of the proposed model and hybrid strategy is verified by computational and analytical results. Several conclusions are yielded.
In high diversity node situation, single-channel MAC protocols suffer from many collisions. To solve this problem, the research of multichannel MAC protocol has become a hotspot. And the cyclic quorum-based multichann...
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In high diversity node situation, single-channel MAC protocols suffer from many collisions. To solve this problem, the research of multichannel MAC protocol has become a hotspot. And the cyclic quorum-based multichannel (CQM) MAC protocol outperformed others owing to its high frequency utilization. In addition, it can avoid the bottleneck that others suffered from and can be easily realized with only one transceiver. To obtain the accurate performance of CQM MAC protocol, a Markov chain model, which combines the channel hopping strategy of CQM protocol and IEEE 802.11 distributed coordination function (DCF), is proposed. The metrics (throughput and average packet transmission delay) are calculated in performance analysis, with respect to node number, packet rate, channel slot length and channel number. The results of numerical analysis show that the optimal performance of CQM protocol can be obtained in saturation bound situation. And then we obtain the saturation bound of CQM system by bird swarm algorithm (BSA). Finally, the Markov chain model and saturation bound are verified by Qualnet platform. And the simulation results show that the analytic and simulation results match very well.
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