Elektrik Yükünün Genetik Algoritma Temelli Holt-Winters Üstel Düzeltme Yönteminiyle Tahmini

Özger, Yunus Emre; Akpınar, Mustafa; Musayev, Zabit; Yaz, Mustafa

doi:10.35377/saucis.02.02.600620

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…Calculates the MSE (Mean Square Error) value and the MAPE (Mean Absolute Presentage Error) value from the 9-day sample data of each tourist spot to see the magnitude of the accuracy of the forecasts generated from each tourist spot studied so that the error value obtained is minimized [15]. maybe, the calculation of MSE and MAPE values is carried out on each data that has calculated the Autoreggressive and Moving Average values then from each MSE and MAPE value in each data it will be averaged so as to produce MSE and MAPE values with a small percentage.…”

Section: Testingmentioning

confidence: 99%

Implementation of Autoregressive Integrated Moving Average for Tourism Recommendation in Pamijahan Area Based on Internet of Things

2023

IJETER

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Pamijahan is one of the sub-districts located in Bogor regency, West Java. Pamijahan has a variety of tourist destinations, one of which is the Cigamea waterfall, Cikuluwung waterfall, and the Seribu watering problem when visiting tourists, one of them is the weather factor such as rainy weather where Bogor has a highland area so very big influence on the variation of rain there and visitors have difficulty in choosing tourist sites with sunny conditions, the solution to the problem above is to predict the weather during rainy weather in the tourist areas of Cigamea waterfall, Cikuluwung waterfall, and Seribu waterfall using the Autoreggressive Integrated Moving Average method as weather prediction process uses Time Series data with the help of the Internet of Things tool in data retrieval, the weather prediction testing process uses the Autoreggressive Integrated Moving Average method by calculating the value of MSE (Mean Square Error) and MAPE (Mean Absolute Presentage Error) as minimum as possible to see the level of accuracy of the weather prediction process at each designated tourist site. The results of this study indicate that weather forecasting in Cigamea, Cikuluwung and Seribu waterfalls shows the smallest MSE (Mean Square Error) value, the waterfall that has the smallest MSE value, the Seribu waterfall with the Mean Square Error value of the temperature sensor 0.06, Air Humidity 0.59, and Light Intensity 13.30, so that tourist attractions that can be used as tourist attractions for visitors are the Seribu Waterfall.

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Section: Testingmentioning

confidence: 99%

Implementation of Autoregressive Integrated Moving Average for Tourism Recommendation in Pamijahan Area Based on Internet of Things

2023

IJETER

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“…PSO is hybridized with GA to improve the efficiency of PSO so that Breeding Swarm (BS) model were introduced [4], however they have some deficiencies. In genetics, to generate a new individual at least two parents are required.…”

Section: Proposed Workmentioning

confidence: 99%

“…With shared experience all particles towards to best solution and search other possibilities through that way. PSO and GA algorithms used in many real-world problems such as wireless sensor optimization and electrical load forecasting [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Effect of the Chaotic Crossover Operator on Breeding Swarms Algorithm

Demirci

Yurtay

2021

Sakarya University Journal of Computer and Information Sciences

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In this paper we present effect of the chaotic crossover operator with different chaotic maps on the metaheuristic search algorithm Breeding Swarms algorithm which is the Particle Swarm Optimization's one of the genetic algorithm hybrid form. Some of the many optimization problems could have too many local extrema. Most of the time optimization algorithms could stuck on these extrema therefore these algorithms could have trouble with finding global extremum. To avoiding local extrema and conduct better search on search space, a chaotic number generator is used on Breeding Swarms algorithm's most of the random procedures. To test efficiency and randomness of the chaotic crossover operator, different chaotic maps are used on the Breeding Swarm algorithm. Test and performance evaluations are conducted on Multimodal and unimodal benchmark functions. This new approach showed us that modified Breeding Swarms algorithm yielded slightly better results than Particle Swarm Optimization and original Breeding Swarms algorithms on tested benchmark functions.

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“…The solution of the insulation problem was researched using different heuristic algorithms by [12,13]. In addition, heuristic algorithms are used in many areas [14,15].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Laminar Boundary Layers in Flow over a Flat Plate Using Recent Metaheuristic Algorithms

2022

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Heat transfer is one of the most fundamental engineering subjects and is found in every moment of life. Heat transfer problems, such as heating and cooling, where the transfer of heat between regions is calculated, are problems that can give exact solutions with parametric equations, many of which were obtained by solving differential equations in the past. Today, the fact that heat transfer problems have a more complex structure has led to the emergence of multivariate models, and problems that are very difficult to solve with differential equations have emerged. Optimization techniques, which are also the subject of computer science, are frequently used to solve complex problems. In this study, laminar thermal boundary layers in flow over a flat plate, a sub-problem of heat transfer, is solved with recent metaheuristic algorithms. Teaching learning-based optimization (TLBO), sine cosine optimization (SCO), gray wolf optimization (GWO), whale optimization (WO), salp swarm optimization (SSO), and Harris hawk optimization (HHO) algorithms are used in the study. In the optimization problem, the laminar boundary layer thickness, heat flow, and distance from the leading edge are determined. These three models’ minimum, maximum, and target values are found under the specified design variables and constraints. In the study, 540 optimization models are run, and it is seen that HHO is the most suitable optimization technique for heat transfer problems. Additionally, SSO and WO algorithms gave results close to HHO. Other algorithms also set model targets with an average of less than 0.07% and acceptable error rates. In addition, the average problem solution time of all optimization algorithms and all models was 0.9 s. To conclude, the recent metaheuristic algorithms are found to be powerful and fast in solving heat transfer problems.

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Elektrik Yükünün Genetik Algoritma Temelli Holt-Winters Üstel Düzeltme Yönteminiyle Tahmini

Cited by 6 publications

References 13 publications

Implementation of Autoregressive Integrated Moving Average for Tourism Recommendation in Pamijahan Area Based on Internet of Things

Implementation of Autoregressive Integrated Moving Average for Tourism Recommendation in Pamijahan Area Based on Internet of Things

Effect of the Chaotic Crossover Operator on Breeding Swarms Algorithm

Optimization of Laminar Boundary Layers in Flow over a Flat Plate Using Recent Metaheuristic Algorithms

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