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Öğe Artificial intelligence approaches to estimate the transport energy demand in Turkey(Springer Heidelberg, 2021) Turgut, Mert Sinan; Eliiyi, Uğur; Turgut, Oğuz Emrah; Öner, Erdinç; Eliiyi, Deniz TürselIn this study, eight parameters are selected and their historical data are collected to predict the future of the energy demand of Turkey. The initial eight parameters were the gross domestic product (GDP) of Turkey, average annual US crude oil price (COP), inflation for Turkey in percentages (INF), the population of Turkey, total vehicle travel in kilometers for Turkey, total amount of goods transported on motorways, employment for Turkey, and trade of Turkey. However, after these eight parameters data are analyzed using Pearson and Spearman correlation methods, it is found out that five of these parameters are highly correlated. The remaining three parameters are the GDP of Turkey, COP, and INF for Turkey. Afterward, five separate scenarios are developed to forecast the future of the energy demand of Turkey. The first two scenarios involve the third- and fourth-order polynomial fitting, the third and fourth scenarios employ static and recurrent neural networks, and the fifth scenario utilizes autoregressive models to predict the future energy demand of Turkey. The efficient hybridization of the seagull optimization and very optimistic method of minimization metaheuristic algorithms is carried out to achieve the polynomial fitting of the data. The optimization performance of the hybrid algorithm is assessed by applying the algorithm on benchmark optimization problems and comparing the results with that of some other metaheuristic optimizers. Moreover, it is seen that the forecasts of the first scenario agree well with the Ministry of the Energy and Natural Resources estimates.Öğe Determination of freezing of gait with wearable sensors in patients with Parkinson's disease(Wiley, 2020) Eliiyi, Uğur; Keskinoğlu, Pembe; Kahraman, Turhan; Özkurt, Ahmet; Yürdem, Betül; Duran, G.; Genç, AslıObjective: The aim was to determine freezing of gait (FOG) with wearable sensors in patients with Parkinson’s disease (PD). Background: PD is a neurodegenerative disorder leading to deficits in automatic motor performance. FOG is a major mobility problem for patients with PD, can be accompanied by postural instability and subsequent falls. Accurate and automatic FOG detection are essential for long-term symptom monitoring or preventing FOG via cueing. Although some studies have investigated the use of wearable sensors to detect FOG, conducted mostly with participants who were mainly in early stages of PD, there is no firm consensus regarding appropriate methodologies. Method: This study had a diagnostic accuracy design. Multi-segmental acceleration data was obtained from 12 patients with PD performing standardized tasks, and clinical assessment of FOG was performed by an experienced neurologist in real time and from video recordings. Three-axis wireless accelerometers were attached to patients’ ankles, waist and wrists. Trials were performed during the drug-free period, at least 12 hours after taking medication. The standardized tasks included standing from a chair, walking, 180o and 360o turnings, and passing a doorway. Trials were repeated at least 3 times, and up to 5 times if there was no FOG event. Sensor signals were processed as numerical data. Results: The mean age of patients was 64 years, 58% of them were males, and mean of disease duration was 10 years. Modified Hoehn and Yahr scale scores ranged from 2.5 to 4. The data matrix dimension is 103,261*18. Random forest (RF), artificial neural network (ANN), and decision tree (DT) methods, which are among the supervised learning algorithms, were used to predict FOG in the presence of misleading tremors on this big data. Algorithms’ performances were AUCRF/ANN/DT= 0.985 / 0.962 / 0.765 and sensitivityRF/ANN/DT= 97.1% / 94.3% / 93.8%. Conclusion: The predictions of ANN and RF were much better, while the sensitivity of DT was close to other methods. FOG detection is important to prevent it before occurring and decrease its effects. In this study, it has been shown that FOG can be detected by using the proposed algorithms with data collected from wearable sensors in patients with PD, even who are in late stages of PD.Öğe Elektrikli otobüsler üzerine karşılaştırmalı bir değerlendirme: İzmir şehir içi saha analizi(2021) Önçağ, Ali Çağlar; Üzkat, Hakan; Yeşil, Ziya Can; Eliiyi, UğurSon yıllarda iklim değişikliği, enerji maliyetleri, egzoz emisyonları gibietkenler nedeniyle elektrikli otobüslerin, dizel otobüslere alternatif olupolamayacağı konusu gündeme gelmektedir. Bu çalışmada elektrikliotobüslerin genel özellikleri incelenmekte ve 12 m uzunluğunda 20araçtan oluşan bir elektrikli otobüs filosunun İzmir içerisinde kullanımısonucunda elde edilen yaklaşık 2.5 yıllık verinin benzer dizel otobüslerleenerji ve akaryakıt tüketimi bakımından genel bir karşılaştırmasıyapılmaktadır. Buna ek olarak seçilen bir hat üzerinde bir dizel otobüsile detaylı karşılaştırma yapılmaktadır. Elektrikli otobüslerle ilgili enbüyük darboğaz dizel otobüslere göre nispeten düşük menzile sahipolmalarıdır. Buna karşın elde edilen veriler ışığında, yakın gelecekteelektrikli otobüslerin dizel otobüslere ciddi bir alternatif olabileceğigörülmektedir.Öğe Intelligent container repositioning with depot pricing policies(Springer International Publishing Ag, 2022) Guven, Ceyhun; Öner, Erdinç; Eliiyi, UğurEmpty container management has always been a crucial issue in the logistics sector. Specifically, the repositioning of empty containers plays an important role in the industry of maritime shipping. Not only has an economic impact on the stakeholders affiliated with the container logistics chains but also has an effect on the society in terms of environment and sustainability as the reduction in the movement of empty containers will also reduce fuel consumption. The main objective of this paper is to minimize the total cost. This total cost includes the cost required for transportation of the empty containers to their depots and the storage cost of these containers in the assigned depots. The types of costs involved in empty container repositioning are defined via the review of the related literature and industrial practices. In this study, a mixed-integer linear programming model is developed that minimizes the total cost require in the repositioning of empty containers. The proposed model determines the storage depot of each empty container considering the depot pricing policies and distances between the port terminals and container depots. Computational results indicate that the proposed model can identify the best alternatives for empty container storage with minimum total cost.Öğe Performance metrics and monitoring tools for sustainable network management(2021) Duman, İbrahim Özden; Eliiyi, UğurNetwork infrastructures comprise the backbone of our modern life, ranging in scale from relatively microlevel settings of offices or university campuses, to macro-level structures such as smart cities or national defense systems. Consequently, effective management of the quality and sustainability of provided services and network infrastructures has grown to be essential for modern service providers. Considering standard features like reliability, availability and maintainability, several questions are identified in this study for network performance management and investment levels of sustainable network infrastructures. We describe various stages of the performance management processes, along with corresponding software tools to measure network efficiency and sustainability for information and communications technologies. Fundamental key performance indicator categories and their definitions are also compiled according to their functions within the network management context. Depending on the importance of services provided on a network, it is necessary to develop different performance management systems for monitoring the infrastructure for different practitioners. The development of required management systems will be possible by integrating the comprehensive compilation of indicators and software tools presented in this study.Öğe Seasonal reservation scheduling with resource costs: A mathematical modeling approach(2021) Eliiyi, UğurIn this study, a novel optimization problem for simultaneous capacity planning and scheduling in reservation scheduling environments is proposed. The problem is important for seasonal reservation systems such as hotel or seat reservations of travel agencies, or operation and treatment reservations in health tourism. The objective of the problem is to maximize the net profit gained from the processed reservations. To the best of our knowledge, the problem was not previously studied. An integer programming model is developed for exact solutions and extensive computational experimentation reveals model performance under different scenarios. The results are analyzed, and managerial implications are discussed.Öğe A sequential workforce scheduling and routing problem for the retail industry: a case study(2022) Özcan, Sel; Uğurlu, Onur; Eliiyi, UğurThis study investigated the operational workforce scheduling and routing problem of a leading international retail company. Currently, the company plans to launch a new product into the Turkish market, which will be used in all its retail stores across the country. For the best marketing outcome, branding of all retail stores needs to be renewed by an outsourced workforce with a minimum of cost and time. We framed this as a workforce scheduling and routing optimization problem. Therefore, a two-stage solution was proposed. The retail stores were partitioned into disjoint regions in the first stage, and the schedules were optimized in the second stage. We employed the k-means clustering algorithm for constructing these regions. Two different heuristic approaches were applied to solve regional scheduling in the second stage of the algorithm since the resulting scheduling problem is NP-hard. Finally, a computational analysis was performed with real data and the results are discussed.
