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Abstract:Hybridizing chaotic evolutionary algorithms with support vector regression (SVR) to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS) algorithm. This paper investigates potential improvements of the TS algorithm by applying quantum computing mechanics to enhance the search information sharing mechanism (tabu memory) to improve the forecasting accuracy. This article presents an SVR-based load forecasting model that integrates quantum behaviors and the TS algorithm with the support vector regression model (namely SVRQTS) to obtain a more satisfactory forecasting accuracy. Numerical examples demonstrate that the proposed model outperforms the alternatives.

Accurate electricity forecasting is still the critical issue in many energy management fields. The applications of hybrid novel algorithms with support vector regression (SVR) models to overcome the premature convergence problem and improve forecasting accuracy levels also deserve to be widely explored. This paper applies chaotic function and quantum computing concepts to address the embedded drawbacks including crossover and mutation operations of genetic algorithms. Then, this paper proposes a novel electricity load forecasting model by hybridizing chaotic function and quantum computing with GA in an SVR model (named SVRCQGA) to achieve more satisfactory forecasting accuracy levels. Experimental examples demonstrate that the proposed SVRCQGA model is superior to other competitive models.

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The importance of this study in bridging the gap between existing research literature works by analysing the influence of green marketing and awareness of the green brand on customer satisfaction of mineral water products. The analysis adopted a quantitative and analytical approach by administering structured questionnaires. The questionnaire developed based on the objectives of the research and the analysis of the relevant literature on green marketing, green brand awareness, and customer satisfaction. The results revealed green marketing had no influence on customer satisfaction in the case of the Pristine 8 + bottled mineral water customers. However, it was found that green brand awareness has a positive influence on customer satisfaction. Green marketing and green brand awareness simultaneously have a positive influence on customer satisfaction of the Pristine 8 + bottled mineral water brand. This study expands the scientific literature by providing empirical evidence on green marketing, green brand awareness on customer satisfaction that also can use as a consideration that might help companies to make decisions that will allow them to surpass their competitors through green marketing and green brand awareness, and to meet their customer satisfaction.