A Hybrid Approach to Time Series Forecasting Based on the Support Vector machine algorithm and Feature Extraction Using Particle Swarm Optimization(PSO)

In recent years, due to the non-linear nature, complexity, and irregularity of time series, especially in energy consumption and climate, studying this field has become very important. Therefore, this study aims to provide a high accuracy and efficiency hybrid approach to time series forecasting. The proposed model is called EMD-DWT-FPSO-SVR (Support Vector Regression- Feature selection with Particle Swarm Optimization-Discrete Wavelet Transform-Empirical Mode Decomposition). In the proposed hybrid approach, the first step is to decompose the signal into the IMF component using the MED algorithm. In the second step, each component is transformed into subsequences of approximation properties and details by converting the Wavelets. In the third step, the best feature is extracted by the PSO algorithm. The purpose of using the PSO algorithm is feature extraction and error minimization of the proposed approach. The fourth step, using time vector regression, has dealt with time series forecasting. Four data sets in two different fields have been used To evaluate the proposed method. The two datasets are Electric Charge of England and Poland, and the other two datasets are related to the temperature of Australia and Belgium. Evaluation criteria include MSE, RMSE, MAPE, and MAE. The evaluation results of the proposed method with other PCA feature extraction algorithms, and comparisons with methods and studies in this field, indicate the proper performance of the proposed approach

CONCEPTUALIZING TOURIST JOURNEY: QUALITATIVE ANALYSIS OF TOURIST EXPERIENCES ON IRCTC

The study examined tourist experiences on IRCTC by conducting qualitative content analysis of 100 online reviews which were divided into Pre-Trip, Entrance, Payment, and Post-Visit stages. The study showed both positive aspects of digital accessibility and affordability alongside negative aspects regarding ticket availability and station infrastructure alongside payment reliability and service consistency. The analysis identified essential improvement zones for digital performance alongside better customer assistance and standardized services which would strengthen overall passenger satisfaction. The study examined IRCTC as well as Tourist Journey and Railway Tourism through Online Booking and Qualitative Research to evaluate Customer Experience and Service Quality and Ticket Availability and Qualitative Tourism Research with Digital Payments and Travel Satisfaction and Tourism Experience in Indian Tourism.  The research stated that how IRCTC excels at digital accessibility and affordable service but points out ticket availability issues along with station infrastructure problems and payment reliability concerns and service consistency problems. The satisfaction of passengers can be improved by implementing digital improvements and enhanced customer support with standardized services to address current gaps. Future investigations must combine quantitative research methods with international railway tourism frameworks to establish strategic service development plans

Evolution of Reservation in India

Reservation is a tool of increasing social diversity in organizations. It is one of the measures taken by the government to establish social justice. Reservation as a tool for socio-economic upliftment was adopted as a short-term measure for specific categories of people who for various reasons were discriminated against and deprived. This policy was adopted as the means to provide opportunities in employment. While the weaker sections should be given due opportunity, it is necessary to break the vicious circle of limited sections cornering the opportunities