Grey relational analysis

Printed circuit board industry plays an important role in Taiwan's economy, but severe inventory stacking and material lacking problems still exist. However, the occurrence of these problems is likely to be decreased via establishing an accurate demand forecasting system. Thus, an Evolving Neural Network (ENN) forecasting model by integrating Genetic Algorithms and Neural Network is developed in this research. Along with trend and seasonal factors considered by Winter's model, effective economical factors are chosen by the Grey Relation Analysis. The numerical data of these factors and actual demand of the past 5 years are input into the training stage of ENN, while the comparison with other models is evaluated on testing stage. The experimental result shows that the performance of ENN is superior to traditional statistical models and Back Propagation Network. The ENN provides a promising solution to the forecasting problem for relevant industries.

Although extensive studies have focused on the impact of different corporate social responsibility (CSR) activities on environmental sustainability, few studies investigated the effects of CSR activities on environmentally sustainable development and green innovation. Yet, as a determinant of environmental strategies, green innovation haven't received much attention. Therefore, this study explored how different CSR dimensions impacts on environmentally sustainable development and further on green innovation. Data were collected from 282 respondents belonging to the manufacturing industries of Pakistan from January 2019 to April 2019; and analyzed by adopting methods of partial least squares structural equation modeling (PLS-SEM) and grey relational analysis. As per study results, all dimensions of CSR were found positively significant towards environmentally sustainable development. Further, the environmentally sustainable development positively enhances green innovation. This research employed an innovative attempt to evaluate the ranking of these constructs by using grey relational analysis whereby it was found that CSR to environment had a stronger effect, whereas CSR to consumer had a weaker impact on environmentally sustainable development. The research findings suggest that CSR activities should be embedded in the organizational environmental strategies for green innovation, as all CSR dimensions had positive relations with environmentally sustainable development.

This research develops a weighted evolving fuzzy neural network for PCB sales forecasting and it includes four major steps: first of all, collecting 15 factors among macroeconomic data, downstream production demand and total industrial production outputs and then using the Grey Relation Analysis (GRA) to select a combination of key factors which have the greatest influence on PCB sales. Secondly, taking the time serial factor into consideration, the Winter’s Exponential Smoothing method is applied to predict the tendency of PCB sales and the influences of seasonal effects. Thirdly, applying historical data to proceed the training of Weighted Evolving Fuzzy Neural Network (WEFuNN) and then forecasts the future PCB sales by the WEFuNN. Finally, compare three kinds of performance measurements for each model. The experimental results reveal that the MAPE for WEFuNN model is 2.11% which is the best compared to others. In summary, the WEFuNN model can be applied practically as a sales forecasting tool in the PCB industry.

Bir işletmenin finansal performansının doğru analiz edilmesi gelecekte verilecek kararları belirlemek adına önem taşımaktadır. Çok sayıda faktör göz önüne alındığından dolayı Çok Kriterli Karar Verme (ÇKKV) yöntemleri finansal performans analizi için uygun birer araç olarak görülmektedir. Bu çalışmada, BİST Kimya, Petrol, Plastik Endeksi’nde (XKMYA) yer alan işletmelerin finansal performansları analiz edilmiş olup, endekste yer alan 24 işletme sıralanmıştır. Belirlenen kriterler Analitik Hiyerarşi Süreci (AHP) yöntemi ile değerlendirilerek kriter ağırlıkları elde edilmiştir. Ardından, işletmelerin performansları, 2015 yılı bilançolarından elde edilen verilere göre, VIKOR, TOPSIS, GRA ve MOORA yöntemleri ile incelenmiş olup sıralanmıştır. Çalışmanın sonucunda 4 farklı ÇKKV yönteminin sonuçları karşılaştırılmıştır.

Öz Bu çalışmanın temel amacı Türkiye Cumhuriyet Merkez Bankası'nın (TCMB) yayımladığı sektör oranları yardımıyla turizm alt sektörlerinin finansal performanslarını ölçmektir. Çalışmada turizm alt sektörlerinin finansal performansları likidite, finansal yapı, varlık kullanım ve kârlılık göstergeleri bağlamında incelenmiştir. Dört temel gösterge kapsamında 32 finansal oran kullanılarak yapılan finansal performans analizinde Gri İlişkisel Analiz yönteminden yararlanılmıştır. Bu kapsamda TCMB sektör oranlarına ulaşılan altı alt sektörün 2012-2014 dönemine ilişkin finansal performansları değerlendirilmiştir. Elde edilen bulgulara göre turizm şirketlerinin finansal performanslarının ölçülmesinde en önemli gösterge finansal yapı, en az etki eden gösterge ise varlık kullanım göstergesidir. Çalışmada ayrıca turizm alt sektörleri performanslarına göre sıralanmıştır. Buna göre genel performans bağlamında en başarılı alt sektörün seyahat acentesi ve ilgili hizmetler sektörü, en başarısız alt sektörün ise deniz yolcu taşımacılığı olduğu saptanmıştır. Göstergeler bazında bakıldığında likidite ve finansal yapı göstergelerinin her ikisi açısından da konaklama alt sektörü en başarılı, deniz yolcu taşımacılığı en başarısız alt sektördür. Varlık kullanım göstergesi açısından en başarılı sektör seyahat acentesi ve ilgili hizmetler sektörü iken, konaklama alt sektörü en başarısız performansa sahiptir. Son olarak kârlılık göstergesi açısından en başarılı sektör seyahat acentesi ve ilgili hizmetler sektörü, en düşük performansa sahip alt sektör ise kara yolcu taşımacılığı olarak saptanmıştır. Anahtar Kelimeler: Turizm Alt Sektörleri, Gri İlişkisel Analiz, Finansal Performans, TCMB Sektör Oranları. Abstract

The main purpose of this study is to measure tourism sub-sectors' financial performance using sectors financial ratios published by Central Bank of the Republic of Turkey (CBRT). Financial performances of the tourism sub-sectors were investigated in the context of liquidity, financial structure, turnover and profitability indicators. Within four indicators 32 financial ratios were used. Gray Relational Analysis (GRA) method was used to measure financial performance. The study covers between the years 2012-2014 of the six sub-sectors (Other passenger land transportation, Sea and other coastal passenger water transport, Accommodation, Food and beverage service activities, Travel agency, tour operator and other reservation service and related activities and Amusement and recreation activities). According to the findings, financial structure is the most important indicator and turnover is the most trivial indicator in the financial performance measurement of that six tourism sub-sectors. In the study also tourism sub-sectors were sorted by the performance according to the result of GRA method. The most successful sector is the travel agency, tour operator and other reservation service and related activities, (others; the second accommodation, the third food and beverage service activities, the forth other passenger land transportation, the fifth amusement and recreation activities) and the most unsuccessful sector is sea and other coastal passenger water transport. When we look at liquidity and financial structure indicators accommodation is the most successful and the sea and other coastal passenger water transfer sub-sector is the most unsuccessful. In terms of asset utilization indicator the most effective sector is travel agency, tour operator and other reservation and related activities, and the most unsuccessful sub-sector is accommodation. Finally in terms of profitability indicator the most successful sub-sector is travel agency, tour operator and other reservation and related activities, and other passenger land transport sub-sector was determined as the most unsuccessful. GİRİŞ Turizm, kültürel, sosyal ve tarihi değerlerin korunmasına yaptığı katkılarının yanı sıra ekonomide yarattığı katma değer, istihdam, döviz girdisi, çarpan etkisi, ödemeler dengesine etkisi ve Gayri Safi Milli Hasılaya (GSMH) katkısı açısından önemli bir sektördür. Turizmin ekonomik etkilerinden yararlanma imkânı ülkelerin altyapı ve üstyapı yatırımları ile mümkün olmaktadır. Turizm sektörü, dünya ekonomisinde 20. yüzyılın ikinci yarısından itibaren en hızlı gelişen ve genişleyen sektörlerden biridir. Çoğunlukla bölgesel veya ulusal kalkınma için bir araç olarak görülen turizm sektörü, gelir, iş alanları, vergi gelirlerinin oluşturulması, ödemeler dengesi problemlerinin hafifletilmesi ve gelişime katkıda bulunmada rol oynayan önemli bir faktör olarak yerini almıştır (Çımat ve Bahar, 2003: 2). Ülkeye döviz getiren,

In this paper the efficiency and output power are considered, as the most important characteristics of the worm gear reducer, and their optimization was performed. As the influencing factors, the viscosity of the lubricant, the input number of revolutions and the current intensity on the control unit, were taken into account. Experimental tests were performed on the basis of the L27 Taguchi orthogonal matrix. Due to multiple output issues, the Grey method was applied. Based on the Grey relational grade using the ANOVA analysis, the optimal combination of factors is A3B2C3 ie. Grey relational grade is the highest for the number of revolutions 2000 min-1, the viscosity of the lubricant 460 mm 2 /s and current intensity of 0.2 A. Also, Grey relational grade was most influenced by the current intensity on the control unit with 72.1%.