A Novel Approach Towards Time of Day Pricing Scheme using Fuzzy Logic Based Consumer Behavior Model

<p class="MDPI17abstract">The accurate forecasting of solar irradiance depends on various uncertain parameters like time of day, temperature, wind speed, humidity, and atmospheric pressure. All these play an important role in calculating PV power output. In this paper, a novel approach for forecasting of solar irradiance using flexible and accurate fuzzy logic and robust multi-linear regression approach has been proposed considering the above mentioned five variables. Based on the simultaneous consideration of those five variables, the solar irradiance is forecasted using the proposed methodology at a particular location in India, and the results are compared with the real time measured value of solar irradiance at that location on the days for which solar irradiance are forecasted. The proposed method is validated by comparing the results with real time data. The error analysis of the fuzzy logic based proposed system shows the root mean square error of 10.011 and mean absolute percentage error of 1.703%, while compared with real time data measured by instruments pyranometer, anemometer etc. The same results are found better while compared with the results obtained using multilinear regression approach.</p>

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A Compensatory Fuzzy Logic Model in Technical Trading

Axioms ◽

10.3390/axioms10010036 ◽

2021 ◽

Vol 10 (1) ◽

pp. 36

Author(s):

Norma P. Rodríguez-Cándido ◽

Rafael A. Espin-Andrade ◽

Efrain Solares ◽

Witold Pedrycz

Keyword(s):

Fuzzy Logic ◽

Technical Analysis ◽

Graphical Analysis ◽

Logic Model ◽

Financial Asset ◽

Financial Assets ◽

Novel Approach ◽

Subjective Assessments ◽

Efficient Prediction ◽

High Degree

This work presents a novel approach to prediction of financial asset prices. Its main contribution is the combination of compensatory fuzzy logic and the classical technical analysis to build an efficient prediction model. The interpretability properties of the model allow its users to incorporate and consider virtually any set of rules from technical analysis, in addition to the investors’ knowledge related to the actual market conditions. This knowledge can be incorporated into the model in the form of subjective assessments made by investors. Such assessments can be obtained, for example, from the graphical analysis commonly performed by traders. The effectiveness of the model was assessed through its systematic application in the stock and cryptocurrency markets. From the results, we conclude that when the model shows a high degree of recommendation, the actual financial assets show high effectiveness.

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Valuation of travel time and departure time choice in the presence of time-of-day pricing

Transportation Research Part A Policy and Practice ◽

10.1016/j.tra.2007.12.002 ◽

2008 ◽

Vol 42 (4) ◽

pp. 577-590 ◽

Cited By ~ 7

Author(s):

Kaan Ozbay ◽

Ozlem Yanmaz-Tuzel

Keyword(s):

Travel Time ◽

Time Of Day ◽

Departure Time ◽

Departure Time Choice ◽

Time Of Day Pricing

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Digital Content Marketing and Tourism Consumer Behavior--Model

PsycTESTS Dataset ◽

10.1037/t81717-000 ◽

2021 ◽

Author(s):

Viju Mathew ◽

Mohammad Soliman

Keyword(s):

Consumer Behavior ◽

Digital Content ◽

Behavior Model ◽

Content Marketing

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Determinants of Environmentally Friendly Consumer Behavior--Model

PsycTESTS Dataset ◽

10.1037/t79731-000 ◽

1997 ◽

Author(s):

Ann P. Minton ◽

Randall L. Rose

Keyword(s):

Consumer Behavior ◽

Environmentally Friendly ◽

Behavior Model

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Using Fuzzy Logic in Test Case Prioritization for Regression Testing Programs with Assertions

The Scientific World JOURNAL ◽

10.1155/2014/316014 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

Ali M. Alakeel

Keyword(s):

Fuzzy Logic ◽

Regression Testing ◽

Test Case ◽

Test Cases ◽

Test Case Prioritization ◽

Software Developers ◽

Novel Approach ◽

History Of ◽

Supporting Tool

Program assertions have been recognized as a supporting tool during software development, testing, and maintenance. Therefore, software developers place assertions within their code in positions that are considered to be error prone or that have the potential to lead to a software crash or failure. Similar to any other software, programs with assertions must be maintained. Depending on the type of modification applied to the modified program, assertions also might have to undergo some modifications. New assertions may also be introduced in the new version of the program, while some assertions can be kept the same. This paper presents a novel approach for test case prioritization during regression testing of programs that have assertions using fuzzy logic. The main objective of this approach is to prioritize the test cases according to their estimated potential in violating a given program assertion. To develop the proposed approach, we utilize fuzzy logic techniques to estimate the effectiveness of a given test case in violating an assertion based on the history of the test cases in previous testing operations. We have conducted a case study in which the proposed approach is applied to various programs, and the results are promising compared to untreated and randomly ordered test cases.

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