A modified shuffled frog leaping algorithm

The part 2 of the algorithm makes it different from other evolutionary multimodal optimization algorithms. The model can assist decision makers to select suitable emergency vehicles and guide them to avoid congested areas. Lathe machines can be classified as manually controlled or automatically controlled.

Therefore, the dyadic wavelet energy time-spectrum method is used to deal with the vibration signal on the basis of the dyadic wavelet transform. In order to improve the SFLA performance on complex optimisation problems, we apply various evolutionary elements, which are involved vertical transportation systems VTS.

Harmony search has been strongly criticized for being a special case of the well-established Evolution Strategies algorithm. Nevertheless, as the result of nonlinear and discrete characteristics of this problem, traditional optimization methods can not solve it effectively.

The combination of global search and local search in memeplex develops the algorithm to approach the optimal solution [ 26 ]. For the unpredictable changes in road conditions caused by accidents, the dispatching strategy is adjusted based on the real-time link travel speed.

Modified shuffled frog leaping algorithm for simulation capability scheduling problem

When the fault occurs, the distribution of signal energy will be changed in each frequency band, and the fault types can be recognized according to the distribution of energy.

The first scenario is a motion reaching a normal operating velocity. According to the review of the literature, link travel speed function can reflect the dynamic changes of road conditions.

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The algorithm has a well-balanced exploration and exploitation ability. This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

EAF could cause fatigue damage and breakage of equipment, resulting in the vibration and noise of rotary machinery, speeding up the bearing wear, and reducing the working efficiency and service life of the machine and may cause the destructive accidents in severe cases.

It is simultaneously achieved via various criteria of performance, earth conscious, technology, intelligence and flexibility Strakosch and Caporale Countries in this algorithm are the counterpart of Chromosomes in GAs and Particles in Particle Swarm Optimization PSO and it is an array of values of a candidate solution of optimization problem.

We propose an alternative approach to this method which is based on machine learning algorithms. Vibration signal from the operation of machinery usually could help diagnosing the operational state of equipment.

The front-end data acquisition consists of an axial flow pump, an acceleration sensor, and a PCI extension for instrumentation PXI data acquisition system. The hybrid models were validated using several performance metrics and compared to the single ANFIS model.

One day was divided into a number of intervals, and dispatching strategy was updated according to link travel time in each interval. In this case the optimal solution contains very fewitems.

However, Fourier transform is not capable when it comes to the analysis of nonstationary vibration signal of the high-speed rotating machinery with relatively lower accuracy. This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Samanta and Al-Balushi [ 23 ] extracted the features of the vibration signals under normal and fault states of the rotating machinery and applied these data to the input of ANN.

Artificial bee colony algorithm Artificial bee colony algorithm is a meta-heuristic algorithm introduced by Karaboga in[24] and simulates the foraging behaviour of honey bees.

Taking the minimum response time as objective, Zografos et al.

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Specifically, the data are divided into training data and test data. Dybala and Zimroz [ 33 ] proposed to diagnose the faults of rolling bearing with the EMD algorithm, which could detect fault at the early stage of bearing failure.

When the bearing fails, the bearing pedestal used to support the bearing will periodically jump and result in the rigid change of the system with an impact effect, thus causing looseness of the bearing pedestal.

In summary, the Bees Algorithm searches concurrently the most promising regions of the solution space, whilst continuously sampling it in search of new favourable regions. It consists of hubs and interchanges on the expressway.

It is often used when the search space is discrete e. This paper proposed a time-frequency feature extraction method named VWC, which combines the vibration severity, dyadic wavelet energy time-spectrum, and coefficient power spectrum CPS of the maximum wavelet energy level. In the scout bee phase which is an analogy of abandoning exhausted food sources in the foraging process, solutions that are not beneficial anymore for search progress are abandoned, and new solutions are inserted instead of them to explore new regions in the search space.

The ANN can be trained to capture the nuances in the input data and to produce estimated outputs accordingly, which in this case would be the estimated voltages and reactive powers. When the possible emergency vehicle selection strategies arethe objective function value of optimal selection strategies obtained by the base algorithm is The algorithm consists of certain operations such as mutation, crossover, and reproduction.

There are three VTS scenarios, a motion reaching a normal operating velocity, and both reaching and not reaching transitional motion. Flow chart of the proposed fault diagnosis. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants.

It was first proposed and applied in water distribution network designed by Eusuff et al. Two similar studies by Chen and Chen and Onwubolu and Kumalo compared the effectiveness of the GA with several solution algorithms in solving machining operating problems.

Comparative results sow the superiority of the proposed optimization method than the other popular methods in the area. The optimization results are also compared with the results of both genetic algorithm (GA), particle swarm optimization (PSO) algorithm, differential evolution (DE) algorithm, multi-objective particle swarm optimization (MOPSO) algorithm, modified shuffled frog leaping algorithm (MSFLA), gravitational search algorithm (GSA), biogeography-based.

shuffled frog leaping algorithm pdf OKelly 2, for example, Campbell 4, Ernst and.

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Shuffled frog leaping algorithm SFLA is a new meta-heuristic evolutionary. Krishnamoorthy elonghornsales.com this paper, a modified shuffled frog-leaping algorithm MSFLA, which is an improved version of memetic algorithm, is proposed for solving the ELD problem.

Shock and Vibration

A. Modified Shuffled Frog Leaping Algorithm In the natural memetic evolution of a frog population, the ideas of the worse frogs are influenced by the ideas of the better frogs, and the worse frogs tend to jump toward the better ones for the possibility of having more foods.

The frog leaping rule. Modified shuffled frog leaping algorithm for multi-objective optimal power flow with FACTS devices. DG Allocation and Sizing in Distribution Network Using Modified Shuffled Frog Leaping Algorithm Topics Distributed Generation (DG), Line Loss Reduction Index, Modified Shuffled Frog Leaping Algorithm (MSFLA), Voltage Profile.

A Self-adaptive Shuffled Frog Leaping Algorithm for Multivariable PID Controller’s Optimal Tuning.

A modified shuffled frog leaping algorithm
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