In previous years, different Lateral thinking optimization techniques have been developed based on evolutionary computation. Many of these methods are inspired by spill out behaviors in nature. In this Paper, a new op...
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ISBN:
(纸本)9781538609668
In previous years, different Lateral thinking optimization techniques have been developed based on evolutionary computation. Many of these methods are inspired by spill out behaviors in nature. In this Paper, a new optimization algorithm based on the law of gravity and mass interactions named as gravitational search algorithm (GSA) is discussed for solving feature selection. In GSA, the searcher agents are a collection of masses which will interact with each other based on the law of motion and Newtonian gravity which gives the binary evolutionary optimized high performance. The detailed feature selection has been discussed in this paper and The GSA method has been compared with some well-known optimized search methods such as GA (Genetic algorithm), PSO (Particle Swarm Optimization).
As a result of gathering information from multiple consumer centers, big data (BD) assists in analyzing traveler patterns and developing a unique marketing plan tailored to the target demographic. BD tourism forecasti...
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As a result of gathering information from multiple consumer centers, big data (BD) assists in analyzing traveler patterns and developing a unique marketing plan tailored to the target demographic. BD tourism forecasting is a relatively new academic field because of the challenges in capturing, gathering, and modeling this sort of data due to its inherent privacy and economic importance. The growth rate of cruise tourists has slowed down after years of rapid expansion. Investing in homeports, cruise ships, and promotional activities carries a growing danger of financial loss. To make investment decisions and prepare for the future, it. is necessary to predict tourism demand. We present the least-squares vector regression (LSVR) model with the gravitationalsearch method for forecasting demand for cruise tourism (FCT) based on BD to improve forecasting performance. As a part of the proposed model forecasting demand for cruise tourism based on big data (FDCT-BD), hyper-parameters of the LSVR model are improved ming an algorithm and by comparing these models with various configuration combinations. This paper forecasts tourist arrivals based on internet BD from a search engine and online review platforms and the comparative advantage of multi-platform forecasting over single-platform forecasting based on online review data. However, the results show that the methodology's recommended framework is successful and that BD may estimate cruise tourist demand with enhanced performance and accuracy 93.8% and 97.9%, respectively.
Permanent Magnet Synchronous Machine has been utilized in numerous applications, especially in WECS. This paper discusses the inner rotor configuration of PMSM i.e. IRPMSM and the design equations have been formulated...
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Permanent Magnet Synchronous Machine has been utilized in numerous applications, especially in WECS. This paper discusses the inner rotor configuration of PMSM i.e. IRPMSM and the design equations have been formulated in terms of design variables or physical parameters. The design formulation of a 500KVA, 3.3KV, 3 phases, 600rpm IRPMSM used in VAWT for WECS has been discussed where;the objective function for design of IRPMSM has been formulated by weight function, while temperature rise, efficiency, regulation and maximum flux density in stator teeth are used as constraints. The parameters estimation of electrical equivalent circuit of PMSM has been done while minimization the error function. With the estimated parameters, the performance of the machine has been estimated. The error function has been formulated using least square method and the error function obtained using output current of the machine. Both the problems have been optimized using GSA and its hybridization with PSO i.e. GSA-PSO. The formulated optimization problems is programmed in MATLAB and results using GSA and GSA-PSO have been obtained with required optimization curved of all the parameters. The sensitivity analyses have been performed using local sensitivity analysis over design parameters of IRPMSM.
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