Air traffic prediction with fuzzy constraints

In view of the deficiencies of poor prediction accuracy, time-consuming and low efficiency of traditional traffic prediction models, fuzzy constraints are introduced into air traffic traffic system to represent some uncertain information in the field of artificial intelligence, and construct a fuzzy constraint-based air traffic flow prediction The fuzzy constraint-based air traffic prediction model is constructed. By analyzing the decision vector, fuzzy parameter vector and fuzzy constraint set, the prediction model is proposed. The air traffic flow prediction model is built by analyzing the decision vector, fuzzy parameter vector and fuzzy constraint set that affect the fuzzy constraint, and proposing the construction process of the prediction model. The experimental results show that the air traffic flow prediction model can be used to predict the air traffic flow. The experimental results show that the improved prediction model is better than the traditional prediction model in predicting air traffic flow. The results show that the improved prediction model has better prediction results, shorter time consumption and higher accuracy than the traditional prediction model.

THE APPROACH TO MEASUREMENT OF REQUIREMENT QUALITY BY APPLICATION OF GENERALIZED PRIORITIZED FUZZY CONSTRAINT SATISFACTION PROBLEM

The requirement quality affects product development at all lifecycle stages, as well as the end product. Poorly defined requirements bring to extended deadlines, increased financial costs, even to project disruption. Current researches related to the good quality of requirements include characteristics of good requirements and the development of new elicitation techniques. Requirement quality evaluation should be tailored both to the professionals and users who defined requirements according to their needs. Therefore, the model is designed for requirement quality measurement based on the characteristics of good requirements by application of the Generalized Prioritized Fuzzy Constraint Satisfaction Problem. The model enables the participation of selected characteristics of good requirements in quality evaluation, according to priorities. The evaluator obtains information if the requirement satisfies the given quality satisfaction threshold based on the degree of fulfillment of selected characteristics of a good requirement. The model is applied to all types of requirements, as well as to the evaluation of requirements at all software development lifecycle stages.

Modularity and Configuration Applied to Product Integrating the IoT Technology

The growth of the IoT (Internet of Things) offers a large number of opportunities for new product development. The adoption of IoT technologies improves the operational efficiency of products and their interaction with humans. The variety of sensors and communication protocols, the increased number of cloud infrastructures and services, not forgetting security challenges induced by the IoT technologies lead the designers to make complex choices in the configuration of an optimal IoT solution. Modularity and design for configuration represent an efficient solution for the design of products adopting the IoT technologies. This paper applies the model of configurable product design, conceptualized as multi-layer fuzzy models, to the product integrating the IoT technology. The layer models are the fuzzy product specification layer, the fuzzy functional network layer, the fuzzy physical layer, and the fuzzy constraint layer. The model discerns the consensual elementary solutions that create common ground for moving toward a global solution. The case study shows the configuration of a connected houseplant sensor.

Truth-Preservation under Fuzzy pp-Formulas

How can non-classical logic contribute to the analysis of complexity in computer science? In this paper, we give a step towards this question, taking a logical model-theoretic approach to the analysis of complexity in fuzzy constraint satisfaction. We study fuzzy positive-primitive sentences, and we present an algebraic characterization of classes axiomatized by this kind of sentences in terms of homomorphisms and direct products. The ultimate goal is to study the expressiveness and reasoning mechanisms of non-classical languages, with respect to constraint satisfaction problems and, in general, in modelling decision scenarios.

Optimasi perencanaan produksi bahan bakar minyak dengan fungsi kendala fuzzy menggunakan metode goal programming

Dalam perencanaan produksi PT. Pertamina (Persero) TBBM Boyolali, perusahaan tersebut hanya mendistribusikan BBM sesuai dengan permintaan SPBU tanpa melakukan perhitungan matematis apakah pendapatan yang diperoleh sudah optimal dengan semua faktor dan kendala yang ada, seperti harga setiap jenis BBM, jam kerja mesin pengisian BBM di New Gantry System (NGS), moda transport mobil tangki, dan tingkat keselamatan mobil tangki. Untuk itu, penelitian ini bertujuan untuk melakukan optimasi perencanaan produksi BBM menggunakan metode goal programming agar perusahaan dapat memperoleh pendapatan yang maksimal dengan memperhatikan faktor-faktor dan kendala yang ada. Metode goal programming merupakan perluasan dari linear programming yang dapat menyelesaikan optimasi dengan banyak tujuan. Pada penelitian ini, selain dengan fungsi kendala biasa, metode goal programming juga digunakan untuk menyelesaikan permasalahan yang sama ditambah dengan satu fungsi kendala fuzzy, yaitu tingkat keselamatan mobil tangki, yang proses defuzzifikasinya meng­gunakan metode mamdani. Hasil penelitian menunjukkan, kedua penyelesaian metode goal pro­gramming baik dengan kendala biasa maupun dengan kendala fuzzy memberikan keluaran jumlah BBM dan jumlah pendapatan yang sama, yaitu produk premium () sebanyak 1016 kl, bio solar () seba­nyak 1200 kl, pertamax () sebanyak 596 kl, dan pertalite () sebanyak 1632 kl dengan pendapatan sebesar Rp33.022.000.000,00. Optimization planning of fuel oil production with fuzzy constraint using goal programming method AbstractIn the production planning of PT. Pertamina (Persero) TBBM Boyolali, it only distributes fuel in accordance with the demand for gas stations without performing mathematical calculations whether the revenue obtained was optimal with all the factors and obstacles that exist, such as the price of each type of fuel, working hours of filling machine fuel in New Gantry System (NGS), transport modes of the tank car, and the tank car’s safety level. Therefore, this study aims to optimize the production planning using goal programming method so that the company can obtain maximum income by considering the factors and constraints. The goal programming method was an extension of linear programming that can accomplish optimization with many goals. In this study, in addition to the ordinary constraint function, goal programming method was also used to solve the same problem which includes one fuzzy constraint, namely the level of tank car safety, which the defuzzification process using Mamdani method. The result of the study shows that solution of goal programming method both with ordinary and fuzzy constraint give the same amount of fuel output and the same amount of revenue, that is premium () as much 1016 kl, bio diesel () as much 1200 kl, pertamax () as much 596 kl and pertalite () as much 1632 kl with the revenue is Rp33.022.000.000,00.