The use of renewable energy sources in the production of electricity has become inevitable in order to reduce the greenhouse gases left in the atmosphere that cause the Earth to warm up. Although countries on a national basis have implemented a number of policies to support electricity generated from renewable energy sources, investments to produce electricity without a license on a local basis are not desirable. Those who want to invest medium and small scale for the most reason expect that this work will be supported by real data. Although the electricity generated by renewable investments is generated by simulation data, these data are not realistic for such investors. In this study, the climatic conditions of the power plant of 1 MW installed in Konya and power plant production data are monitored. The artificial neural network (ANN) can achieve a high value for accuracy, but these values are sometimes complex and unclear. In the literature, a number of studies have been conducted using different methods to overcome such problems. Real-time solar power plant (SPP) data were used to determine the feasibility and success of the proposed method. The variable neighborhood search (VNS) metaheuristic method was used to acquire the optimal values belonging to input vectors, G h , which were maximized to the value of the fitness function Fs belonging to output class node s. The results obtained by the VNS method showed that the proposed method has the potential to produce the correct rules. Generally, energy investors are curious about the return on their investment. It is very important for energy providers to estimate how much electricity will be generated from existing solar power plants and accordingly determine the measures they will take to meet the electricity demand in the future. In this study, the performance estimation value obtained from the solar power plant depending on the weather conditions was obtained with 95.55% accuracy.

Abstract-Learning logical relations from examples expressed as first order facts has been studied extensively by the Inductive Logic Programming research. Learning with positive-only data may cause over generalization of examples leading to inconsistent resulting hypotheses. A learning heuristic inferring specific generalization of strings based on unique match sequences is shown to be capable of learning predicates with string arguments. This paper describes an inductive learner based on the idea of specific generalization of strings, and the given clauses are generalized by considering the background knowledge.

The concept of "Virtual Reality" has entered our lives by adding virtual reality glasses to the computers, smartphones, or tablets that we frequently use with the developing technology day by day. Virtual reality includes the virtual world and three-dimensional virtual objects created in the computer environment. Virtual Reality technology aims to enable people to interact with objects by immersing them in the virtual world through equipment (VR glasses, hand controls, treadmills, etc.). This technology can be used in education, health, shopping, etc. used, in many fields. In this paper, virtual reality technol-ogy was used in an automobile store application. The study aims to enable people to read the necessary information about the selected automobile by choosing a car and color. Users will be able to visit and interact with this auto shop with virtual reality equipment in their environment. The 3D models required for the study were made with the Blender program, the software was made with the Unity3D game engine, and the application was developed. The application was tested with the participation of 26 people. As a result, the feedback received from users has been positive. It is thought that the study will be developed and contribute to the literature in different ways.

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With the development of autonomous development technology, the need for additional applications to be used inside and outside the vehicle is increasing. As a result of the literature review, many applications have been developed to display vehicle data directly on the monitor, with reflections on glass, and on hardware devices. These applications have been developed only for a defined problem and for a particular autonomous system. In this study, a basic autonomous vehicle software infrastructure and mobile Augmented Reality application that can work on Android devices have been developed. The Mobile Augmented Reality app serves inside and outside the vehicle. In addition, this application has been shown to support multiple autonomous system infrastructures.