Using hybridized ANN-GA prediction method for DOE performed drying experiments

Abstract

Coal is an important component in the energy industry and plays a key role in energy-producing facilities. Moisture is a common condition that has a considerable impact on coal. Coal drying has long been a question of great interest in a wide range of fields. Defining parameters in the coal drying is obtained by experiments. High costs, time constraints, and repetition of an experiment are one of the most frequently stated problems with experimental works. Using qualitative methods with experiments can be more useful for identifying and characterizing the coal drying process. The purpose of this article is finding the effective parameters in the coal drying process by using a hybridized prediction method. Genetic Algorithm (GA) and Artificial Neural Network (ANN) are hybridized with each other to identify and characterize the coal drying process. GA-ANN algorithm is applied to the coal drying process to predict the moisture of coal, but it does not provide a decent result at first. Later, the Design of Experiment (DoE) methodology is performed to determine the main effects of six parameters. Two scenarios are generated because two parameters are not statistically significant. The first scenario excludes the air relative humidity parameter, and the second scenario excludes the air relative humidity and the velocity of air parameters. Following the application of the DoE method, GA-ANN reaches decent results in scenario-2.     

新颖型非整体膜结构硅加速度计的研制

简要介绍了利用硅的各向异性腐蚀工艺研制的非整体膜结构的敏感硅芯片，较详细地报告了用此硅芯片封装成的加速度敏感元件，最后介绍这种加速度计的优良性能。     

水质自动监测记录仪的研制

指出了国内环保部门在水质监测方面存在的问题，阐述了研制水质自动监测仪的必要性。文中对该仪器的硬件和软件组成做了详细的介绍。同时对它的技术创新之处做了较详细的说明。     

Passenger Flow Prediction Based on Newly Adopted Algorithms

Passenger flow forecasting is an essential part of transportation systems. Neural networks in the transportation field have been applied to passenger demand prediction. In this paper, we developed two hybrid methods, known as parlimentary optimization algorithm-artificial neural network (POA-ANN), and intelligent water drops algorithm-ANN (IWD algorithm-ANN). In addition, we applied the proposed algorithms to illustrate the effect of precise prediction for passenger queues. We mainly focus on predicting passenger demand by comparing the genetic algorithm-ANN (GA-ANN) with POA-ANN and IWD-ANN. The results of prediction methods suggest that both POA-ANN and IWD-ANN provide a better forecasting performance, which is obtained via mean square error (MSE), than GA-ANN in the field of passenger flow prediction. This study illustrates that the newly adopted algorithms exhibit good performance for passenger prediction.     

An intelligent process planning system for prismatic parts using STEP features

This paper presents an intelligent process planning system using STEP features (ST-FeatCAPP) for prismatic parts. The system maps a STEP AP224 XML data file, without using a complex feature recognition process, and produces the corresponding machining operations to generate the process plan and corresponding STEP-NC in XML format. It carries out several stages of process planning such as operations selection, tool selection, machining parameters determination, machine tools selection and setup planning. A hybrid approach of most recent techniques (neural networks, fuzzy logic and rule-based) of artificial intelligence is used as the inference engine of the developed system. An object-oriented approach is used in the definition and implementation of the system. An example part is tested and the corresponding process plan is presented to demonstrate and verify the proposed CAPP system. The paper thus suggests a new feature-based intelligent CAPP system for avoiding complex feature recognition and knowledge acquisition problems.     

Type-2 fuzzy model based controller design for neutralization processes

In this study, an inverse controller based on a type-2 fuzzy model control design strategy is introduced and this main controller is embedded within an internal model control structure. Then, the overall proposed control structure is implemented in a pH neutralization experimental setup. The inverse fuzzy control signal generation is handled as an optimization problem and solved at each sampling time in an online manner. Although, inverse fuzzy model controllers may produce perfect control in perfect model match case and/or non-existence of disturbances, this open loop control would not be sufficient in the case of modeling mismatches or disturbances. Therefore, an internal model control structure is proposed to compensate these errors in order to overcome this deficiency where the basic controller is an inverse type-2 fuzzy model. This feature improves the closed-loop performance to disturbance rejection as shown through the real-time control of the pH neutralization process. Experimental results demonstrate the superiority of the inverse type-2 fuzzy model controller structure compared to the inverse type-1 fuzzy model controller and conventional control structures.     

Enhancement of interlaminar fracture toughness of carbon fiber–epoxy composites using polyamide‐6,6 electrospun nanofibers

In this study, carbon fiber–epoxy composites are interleaved with electrospun polyamide‐6,6 (PA 66) nanofibers to improve their Mode‐I fracture toughness. These nanofibers are directly deposited onto carbon fabrics before composite manufacturing via vacuum infusion. Three‐point bending, tensile, compression, interlaminar shear strength, Charpy impact, and double cantilever beam tests are performed on the reference and PA 66 interleaved specimens to evaluate the effects of PA 66 nanofibers on the mechanical properties of composites. To investigate the effect of nanofiber areal weight density (AWD), nanointerlayers with various AWD are prepared by changing the electrospinning duration. It is found that the electrospun PA 66 nanofibers are very effective in improving Mode‐I toughness and impact resistance, compressive strength, flexural modulus, and strength of the composites. However, these nanofibers cause a decrease in the tensile strength of the composites. The glass‐transition temperature of the composites is not affected by the addition of PA 66 nanofibers. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 45244.     

Cu, Cr and As distribution in soils adjacent to CCA-treated utility poles in Eastern Blacksea Region of Turkey

In this study, the main objective was to asses the distribution of Cu, Cr, and As in soils adjacent to CCA-treated utility poles in Eastern Blacksea Region of Turkey (Trabzon, Rize and Artvin ) and determine the influence of soil composition.

Surface (0–5 cm) and subsurface soil samples (30–40 cm) were collected near CCA-treated utility poles and control soil samples away from CCA-treated utility poles were also collected. Water holding capacity, pH and mechanical properties of soil samples were determined for both depth levels.

Results showed that Cu, Cr and As concentration in soil samples taken from all three cities in 0–5 cm depth was higher than soil samples taken from 30–40 cm depth. Cu, Cr and As concentrations were much higher in soil samples taken from city of Rize     

Buckling lengths of irregular frame columns

In several design codes and specifications, simplified formulae and diagrams are given for determining the buckling lengths of frame columns. It is shown that these formulae may yield rather erroneous results, especially for irregular frames. This is due to the fact that the code formulae utilise only local stiffness distributions. In this paper, a simplified procedure for determining approximate values for the buckling loads of both regular and irregular frames is developed. The procedure utilises lateral load analysis of frames and yields errors on the order of 5%, which may be considered suitable for design purposes. The proposed procedure is applied to several numerical examples and it is shown that all the errors are in the acceptable range and on the safe side.     

The effect of additives on the oxidation stability of biodiesel

In the present study, it was aimed to examine the degradation of biodiesel and the changes that occur in the cold flow characteristics of biodiesel obtained from safflower oil as a result of the modification of the production process steps that leads to a state in which the process is not realized completely despite the addition of antioxidant additives that stabilize the cold flow characteristics of the fuel and the effects of the modification of the production process steps on fuel characteristics. The study is focused on the modification of the production process. Some samples showed very rapid decomposition in the first 3 hours but the rest took nearly 3 days to reach 200 microsiemens. But then the derivative this value due to the rate of oxidation 0.04 h showed.