This paper describes a reverse engineering methodology so as to accomplish an aero-propulsive modelling (APM) through implementing a drag polar estimation for a case study jet aircraft in case of the absence of the th...
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This paper describes a reverse engineering methodology so as to accomplish an aero-propulsive modelling (APM) through implementing a drag polar estimation for a case study jet aircraft in case of the absence of the thrust data of the aircraft's engine. Since the available thrust force can be replaced by the required thrust force for the sustained turn, this approach allows the elimination for the need of the thrust parameter in deriving an aero-propulsive model utilising equations of motion. Two different modelling approaches have been adopted: (i) implementing the 6-DOF model data for sustained turn and climb flight to achieve induced drag model;and then incorporating the glide data to obtain the total drag polar model;(ii) using the 6-DOF model data together with introducing the effect of C L -alpha dependency. The error assessments showed that the derived CSA models were able to predict the drag polar values accurately, providing linear correlation coefficient (R) values equal to 0.9982 and 0.9998 for the small alpha assumption and C L -alpha dependency, respectively. A direct comparison between the trimmed C D values of 6-DOF model and the values predicted by the CSA model was accomplished, which yielded highly satisfactory results within high subsonic and transonic C L values.
As technology advances, the services provided by domain servers require new innovative techniques that can be optimized for frequent changes. Man-in-the-Middle (MitM) attacks on Domain Name Servers (DNS) pose a securi...
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As technology advances, the services provided by domain servers require new innovative techniques that can be optimized for frequent changes. Man-in-the-Middle (MitM) attacks on Domain Name Servers (DNS) pose a security threat, enabling attackers to intercept, modify, and redirect network traffic to malicious sites or users. This study designed an anomaly-based detection scheme that identifies and mitigates MitM attacks on DNS. The proposed model utilizes machine learning algorithms and statistical analysis techniques to ensure that the analysis of DNS query patterns can efficiently detect anomalies associated with the MitM. By integrating the cuckoo search algorithm, the scheme minimizes false positives while improving the detection rate. The Proposed scheme was evaluated using the Internet of Things Intrusion Detection (IoTID) and Intrusion Detection System (IDS) datasets, achieving a detection accuracy of 99.6% and demonstrating its effectiveness in minimizing the MitM attacks on DNS.
The objective of image segmentation is to extract meaningful objects. A meaningful segmentation selects the proper threshold values to optimize a criterion using entropy. The conventional multilevel thresholding metho...
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The objective of image segmentation is to extract meaningful objects. A meaningful segmentation selects the proper threshold values to optimize a criterion using entropy. The conventional multilevel thresholding methods are efficient for bi-level thresholding. However, they are computationally expensive when extended to multilevel thresholding since they exhaustively search the optimal thresholds to optimize the objective functions. To overcome this problem, two successful swarm-intelligence-based global optimization algorithms, cuckoosearch (CS) algorithm and wind driven optimization (WDO) for multilevel thresholding using Kapur's entropy has been employed. For this purpose, best solution as fitness function is achieved through CS and WDO algorithm using Kapur's entropy for optimal multilevel thresholding. A new approach of CS and WDO algorithm is used for selection of optimal threshold value. This algorithm is used to obtain the best solution or best fitness value from the initial random threshold values, and to evaluate the quality of a solution, correlation function is used. Experimental results have been examined on standard set of satellite images using various numbers of thresholds. The results based on Kapur's entropy reveal that CS, ELR-CS and WDO method can be accurately and efficiently used in multilevel thresholding problem. (C) 2013 Elsevier Ltd. All rights reserved.
This study proposes a cuckoo search algorithm (CSA) for solving non-convex economic dispatch (ED) considering generator and system characteristics including valve-point effects, multiple fuels, prohibited zones, spinn...
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This study proposes a cuckoo search algorithm (CSA) for solving non-convex economic dispatch (ED) considering generator and system characteristics including valve-point effects, multiple fuels, prohibited zones, spinning reserve and power loss. CSA is a new meta-heuristic optimisation method inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species. When the host birds discover an alien egg in their nest, they can either throw it away or simply abandon their nest and build a new one elsewhere. The CSA idealised such breeding behaviour in combination with Levy flights behaviour of some birds and fruit flies for applying to various constrained optimisation problems. The effectiveness of the proposed method has been tested on different non-convex ED problems. Test results have indicated that the proposed method can obtain less expensive solutions than many other methods reported in the literature. Accordingly, the proposed CSA is a promising method for solving the practical nonconvex ED problems.
As the demand for renewable energy sources continues to grow, optimizing the efficiency of solar photovoltaic (PV) systems becomes increasingly important. This study illustrates a solar PV system that determines maxim...
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This paper introduces a novel optimized brightness preserving histogram equalization approach to preserve the mean brightness and to improve the contrast of low-contrast image using cuckoo search algorithm. Traditiona...
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This paper introduces a novel optimized brightness preserving histogram equalization approach to preserve the mean brightness and to improve the contrast of low-contrast image using cuckoo search algorithm. Traditional histogram equalization scheme induces extreme enhancement and brightness change ensuing abnormal appearance. The proposed method utilizes plateau limits to modify histogram of the image. In this method, histogram is divided into two sub-histograms on which histogram statistics are exploited to obtain the plateau limits. The sub-histograms are equalized and modified based on the calculated plateau limits obtained by cuckoosearch optimization technique. To demonstrate the effectiveness of proposed method a comparison of the proposed method with different histogram processing techniques is presented. Proposed method outperforms other state-of-art methods in terms of the objective as well as subjective quality evaluation.
This paper presents a novel emission/reliable/economic dispatch (ERED) problem using a newly developed multi-objective cuckoo search algorithm (CSA). Traditionally, electric power systems are operated in such a way th...
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This paper presents a novel emission/reliable/economic dispatch (ERED) problem using a newly developed multi-objective cuckoo search algorithm (CSA). Traditionally, electric power systems are operated in such a way that the total fuel cost is minimized regardless of the emission and reliability level of the system. Recently, the restructured power system stresses the need for non-polluting, reliable, and economic operation. Hence, three conflicting objective functions such as emission, reliability, and fuel cost functions are considered in the practical economic dispatch (ED) problem. The ERED problem is formulated as a non-smooth and non-convex multi-objective ED problem incorporating valve-point effects of thermal units. The CSA utilizes the breeding behaviour of cuckoos, where each individual searches the most suitable nest to lay an egg (compromise solution) in order to maximize the egg's survival rate and achieve the best habitat society. The fuzzy set theory is used to find a best compromise solution from the Pareto-optimal set. The effectiveness of the proposed methodology is tested on a benchmark of 6-unit test system, IEEE RTS 24 bus system, and IEEE 118 bus system. The results are validated and compared with the solution available in the existing literature.
This paper proposes a cuckoo search algorithm (CSA) for solving short-term fixed-head hydrothermal scheduling (HTS) problem considering power losses in transmission systems and valve point loading effects in fuel cost...
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This paper proposes a cuckoo search algorithm (CSA) for solving short-term fixed-head hydrothermal scheduling (HTS) problem considering power losses in transmission systems and valve point loading effects in fuel cost function of thermal units. The CSA method is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species for solving optimization problems. The advantages of the CSA method are few control parameters and effective for optimization problems with complicated constraints. The effectiveness of the proposed CSA has been tested on different hydrothermal systems and the obtained test results have been compared to those from other methods in the literature. The result comparison has shown that the CSA can obtain higher quality solutions than many other methods. Therefore, the proposed CSA can be an efficient method for solving short-term fixed head hydrothermal scheduling problems. (C) 2014 Elsevier Ltd. All rights reserved.
The Interval Type-2 Fuzzy Logic Controller (IT2FLC) is an advanced version of Type-1 Fuzzy Logic Controller (T1FLC) that improves the control strategies by using the advantage of its footprint of uncertainty of the Fu...
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The Interval Type-2 Fuzzy Logic Controller (IT2FLC) is an advanced version of Type-1 Fuzzy Logic Controller (T1FLC) that improves the control strategies by using the advantage of its footprint of uncertainty of the Fuzzy Membership Function (MF). Numerous experimental investigations have shown the superiority of IT2FLC over T1FLC, particularly in high level of uncertainties and nonlinearities. Nevertheless, the systematic design of IT2FLCs remains an attractive problem because of the difficulty in finding the parameters associated with IT2FLCs. In this study, a novel application of cuckoosearch (CS) algorithm in the design of an optimized cascade Interval Type-2 Fuzzy Proportional Integral Derivative Controller (IT2FPIDC) is presented. The PID gains and the parameters of the antecedent MFs of IT2FPIDC are optimized using CS algorithm. Considering the higher number of parameters to be optimized in cascade IT2FPIDC, the CS method was employed due to its high convergence speed and less computational cost. The proposed CS based cascade optimized IT2FPIDC is compared with CS-based Type-1 Fuzzy Proportional Integral Derivative Controller (T1FPIDC). The present research presents a new application of proposed CS based cascade optimized IT2FPIDC for the balancing control and trajectory tracking control of the Furuta pendulum (FP) which is a nonlinear, non-minimum phase and unstable system. Furthermore, the disturbance rejection ability of the proposed controller is analyzed. The proposed control strategies are evaluated on FP produced by Quanser through numerous experimentations in the real world as well as simulation. The performance characteristic considered for these controllers are settling time (t(s)), steady state error (E-ss), rise time (t(r)) and maximum overshoot (M-p). Both the simulation and real world experiments results demonstrated the robustness and effectiveness of the proposed CS based IT2FPIDC with respect to parameter variation, noise effects and load dis
This paper proposes a cuckoo search algorithm (CSA) for solving for the combined heat and power economic dispatch (CHPED) problem considering valve point loading effects on fuel cost function of pure power generation ...
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This paper proposes a cuckoo search algorithm (CSA) for solving for the combined heat and power economic dispatch (CHPED) problem considering valve point loading effects on fuel cost function of pure power generation units and electrical power losses in transmission systems. The main objective of the CHPED problem is to minimize the total fuel cost for producing electricity and heat supplying to a load demand. The proposed CSA method inspired from the reproduction behavior of cuckoo birds has attracted many researchers implementing to engineering optimization problems since it has showed several advantages of few control parameters, high solution quality and fast computational time. The effectiveness and robustness of the proposed CSA have been validated on five different systems including three systems with quadratic fuel cost function of pure power units neglecting transmission losses and two systems with nonconvex fuel cost function of pure power units. The result comparisons between the CSA method and other methods for the test systems have revealed that the CSA method can obtain higher quality solution with faster computational time than many other methods. Therefore, the proposed CSA method can be a very efficient method for solving the CHPED problem. (C) 2016 Elsevier Ltd. All rights reserved.
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