Engineering Commons^™

Research On Fuzzy Control And Optimization For Traffic Lights At Single Intersection, Jiajia Liu, Xingquan Zuo

Journal of System Simulation

Abstract: Aiming at the traffic signal control at urban single intersection,a fuzzy control method for traffic lights is presented.The method is based on a four-phase phasing sequence to control the traffic lights at a single intersection.Inputs of the fuzzy controller are the number of vehicles in line and the arrival rate of vehicles,and the output is the green light extension time of the current green light phase.A genetic algorithm (GA) is used to optimize fuzzy rules and membership functions of the fuzzy control system to improve the performance of the fuzzy controller.The fuzzy control method is realized by using …

Mono And Multi-Objective Optimization And Modeling Of Machining Performance In Face Milling Of Ti6al4v Alloy, Al Mazedur Rahman

Theses and Dissertations

Titanium alloys are extensively used in numerous industries like aerospace, automotive, military, etc., due to their exclusive characteristics. But machining these alloys has always been challenging for manufacturers. This research investigates the effect of radial depth of cut on cutting forces, tool life, surface roughness (Ra), and material removal rate (MRR) during face milling of Ti6Al4V alloy. It also aims to perform mono and multi-objective optimization of response characteristics to determine the optimal input parameters, namely cutting speed, feed rate, and radial depth of cut. Taguchi method and analysis of variance (ANOVA) have been used for mono-objective optimization, whereas Taguchi-based …

Heat Transfer Modeling And Optimization Of A Carbonized Microvascular Solar Receiver, Taylor Brown

Boise State University Theses and Dissertations

Concentrating solar power is an emerging renewable energy source. The technology can collect and store thermal energy from the sun over long durations, generating electricity as needed at a later time. Current CSP systems are limited to a maximum operational temperature due to constraints of the working fluid, which limits the maximum possible efficiency of the system. One proposed pathway forward is to utilize a gas phase for the working fluid in the system such as supercritical carbon dioxide.

A composite gas phase modular receiver is being developed by researchers at Boise State University and the University of Tulsa. The …

Research Of The Characteristics Of The Information Stream Transmission Channel Based On A Hybrid Neural Network, Z.Z. Nigmatov, Sh.S. Karimov

Chemical Technology, Control and Management

The article describes a hybrid algorithm for tuning parameters of a neural network based on sigma-pi neurons. The process of controlling an algorithm based on a hybrid neural network is considered. The use of an integrated training approach for neural networks built on the basis of sigma-pi neurons makes it possible to train them in the time required to configure the neural network to solve an applied problem. The possibility of using a sigma-pi network to estimate the parameters of the information transmission channel based on the analysis of the spectrum of the reflected sounding signal is considered. To form …

Research On A Novel Biogeography-Based Optimization Algorithm Based On Ga, Wang Ning, Lisheng Wei

Journal of System Simulation

Abstract: In order to further improve the optimization ability of biogeography-based optimization algorithm, a new genetic algorithm is proposed. The selection operation is added before the migration operation, and the migration individual is selected by the method of "roulette", so that the individuals with higher fitness can be preferentially migrated. The mutation operation combines the genetic gaussian mutation method, and the optimization performance of the algorithm is improved. The convergence condition of the method is derived in theory. Five test functions are used in the experiments, and the results prove that the ameliorated algorithm is better at the results of …

Operation Loss Reduction Control For Large-Scale Wind Farm Based On Hybrid Modeling Simulation, Yunqi Xiao, Wang Yi

Journal of System Simulation

Abstract: Due to the large number of transformers and collection lines in large-scale wind farms, the losses of collecting system is serious in actual operation. A reactive power/voltage control strategy is proposed, which takes wind turbines as the distributed reactive power sources to optimize the power flow in wind farm and reduce the overall losses of collector system. To improve the efficiency of wind farm modeling and multi-scene loss reduction simulation, a hybrid modeling and simulation scheme based on combining object model configuration and control algorithm programming is proposed. The wind farm model consists of module configuration, and can be …

Simulation Of Grid-Connected Solar Micro-Inverter Based On Fuzzy Pi Controller And Feed-Forward Compensation, Weiliang Liu, Changliang Liu, Huichao Zhang, Yongjun Lin, Liangyu Ma

Journal of System Simulation

Abstract: Grid-connected solar micro-inverter is a highly nonlinear and time-varying system, so it is difficult to achieve good control effect using traditional PI controller. Small signal analysis model of micro-inverter was established, grid-connected current control strategy composed of fuzzy PI controller and grid voltage feed-forward was put forward, and the initial parameters of PI controller was optimized using the genetic algorithm. Simulation results show that the control strategy has the virtues of good robustness, small dynamic deviation, and could reduce the harmonic content of grid-connected current.

A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Electric Vehicles (EVs) and charging infrastructure are starting to become commonplace in major cities around the world. For logistics providers to adopt an EV fleet, there are many factors up for consideration, such as route planning for EVs with limited travel range as well as long-term planning of fleet size. In this paper, we present a genetic algorithm to perform route planning that minimises the number of vehicles required. Specifically, we discuss the challenges on the violations of constraints in the EV routing problem (EVRP) arising from applying genetic algorithm operators. To overcome the challenges, techniques specific to addressing the …

Multiresolution Scene Matching Algorithm For Infrared And Visible Images Based On Non-Subsampled Contourlet Transform, Liu Gang, Guangyu Wang, Zhou Heng, Mingjing Wang

Journal of System Simulation

Abstract: Aiming at scene matching problem for taking infrared image as the actual data and the visible image as the referenced data, a multiresolution matching algorithm was proposed based on non-subsampled contourlet transform (NSCT). By using the transform of phase congruency transform, the difference of grayscale and contrast between infrared image and visible light image was weakened. Subsequently, the two types of images were separately transformed into non-subsampled contourlet domain and the proposed method took the Krawtchouk invariant moment as matching feature. The presented method, which used the improved genetic algorithm (GA) as searching strategy which conquered the precocious phenomenon, …

Improved Genetic Algorithm-Based Network Game Path Selection And Simulation, Jianping Gu, Mingmin Zhang, Meiliang Wang

Journal of System Simulation

Abstract: Traditional optimal path algorithm only sets the shortest path as the target, and it does not consider the network congestion and the number of users in game area for real-time situation, thus resulting in some limitations. According to the actual circumstance of network game, network game path selection model was proposed, and the improved genetic algorithm was employed for simulation. The method pre-processed the game map to get each road weighted length value for a real-time game map, and optimization solution was obtained through the genetic algorithm. A network game path selection method based on improved genetic algorithm was …

Vehicle Routing Optimization Model Of Cold Chain Logistics Based On Stochastic Demand, Xiangguo Ma, Tongjuan Liu, Pingzhe Yang, Rongfen Jiang

Journal of System Simulation

Abstract: The costs of vehicle distribution in the process of cold chain logistics is analyzed and amended; A mathematical model with mixing time window is built to balance the customers' service request with importance level; To minimize the total cost, a mathematical model which uses a factor to make balance between the stability of customer demand fluctuation and the cost increase in the assignment phase is established. Based on MATLAB software, the optical solution is found with adaptive genetic algorithm by taking the background of a distribution center to simulate and analyze.

Structure Learning Of Fuzzy-Tree Based On Rigorous Binary Tree Code And Genetic Algorithm, Changliang Liu, Ziqi Wang

Journal of System Simulation

Abstract: To solve the problems of information redundancy and low optimization efficiency in the structure learning of fuzzy-tree model, a method based on rigorous binary tree code and genetic algorithm is proposed. The structure of fuzzy-tree model is coded by rigorous binary tree code, which improves the information redundancy of the existing matrix code. Considering the particularity of the code and the convergence of the algorithm, an improved genetic algorithm is proposed to optimize the structure of fuzzy-tree model. The experimental results show that the algorithm has good stability and computing speed on different data sets, and can find a …

3d Printing Orientation Optimization Based On Non-Dominated Sorting Genetic Algorithm, Dai Ning, Lisong Ou, Renkai Huang, Liu Hao

Journal of System Simulation

Abstract: Part orientation is one of the key technologies in 3D Printing,which has important influence on the surface precision, machining time and machining cost of the part. This problem is a research hot point of how to balance the surface precision and machining time. The improved Non-dominated Sorting Genetic algorithm was proposed to solve the problem of part orientation optimization. The mathematical model of part surface accuracy and machining time were constructed. The chromosome model of part orientation and the adaptive crowding distance were established. The genetic operators of select, crossover and mutation were used to get a set of …

Boiler Combustion Optimization Based On Bayesian Neural Network And Genetic Algorithm, Haiquan Fang, Huifeng Xue, Li Ning, Fei Xi

Journal of System Simulation

Abstract: Neural network and genetic algorithm have been extensively used in boiler combustion optimization problems. But the traditional Back Propagation neural network's generalization ability is poor. The Bayesian regularization can improve the neural network's generalization ability. A boiler combustion multi-objective optimization method combining Bayesian regularization BP neural network and genetic algorithm （Bayes NN-GA）was researched. A number of field test data from a boiler was used to simulate the Bayesian neural network model. The results show that the thermal efficiency and NOx emissions predicted by the Bayesian neural network model show good agreement with the measured, and the optimal results show …

Investigation Of Strength And Fatigue Life Of Rubber Asphalt Mixture, Jiang Yuan, Songtao Lv, Xinghai Peng, Lingyun You, Milkos Borges Cabrera

Michigan Tech Publications

Strength and fatigue life are essential parameters of pavement structure design. To accurately determine the pavement structure resistance of rubber asphalt mixture, the strength tests at various temperatures, loading rate, and fatigue tests at different stress levels were conducted in this research. Based on the proposed experiments, the change law of rubber asphalt mixture strength with different temperatures and loading rates was revealed. The phenomenological fatigue equation of rubber asphalt mixture was established. The genetic algorithm optimized backpropagation neural network (GA-BPNN) is highly reliable for optimizing production processes in civil engineering, and it has a remarkable application effect. A GA-BPNN …

Optimization Model Of Cis Network Architecture Based On Information Flow, Jianhua Li, Junwei Zhao

Journal of System Simulation

Abstract: In order to explore the internal relationship between Command Information System (CIS) network and combat system, a layered combat system model was built, including organizational relationship layer, information interaction layer and communication link layer. Conception of the system coupling intensity was defined, which reflected the influence of network architecture to combat system. An optimization model of CIS network architecture aimed at maximizing the ratio of system coupling intensity to cost coefficient was built. A route programming genetic algorithm was designed and applied into simulation of Air Offensive Campaign (AOC) system network. The results show that the model and algorithm …

Cell Voltage Optimization Of Aluminum Electrolysis Based On Neural Network-Genetic Algorithm, Chenhua Xu, Li Zhi

Journal of System Simulation

Abstract: In order to reduce the production cost of electrolytic aluminum, an optimization extreme method was proposed based on neural network and genetic algorithm, to find the optimal production cell voltage and the corresponding production conditions. Using kernel principal component analysis method to determine the key parameters affecting of aluminum electrolysis production, a neural network model of electrolytic aluminum was established. Using the genetic algorithm, the global optimal value of the cell voltage of the electrolytic aluminum and the corresponding production conditions were found. The simulation results show that the neural network and genetic algorithm can predict the cell …

Study On Aircraft Scheduling Optimization Based On Improved Genetic Algorithm, Yaohua Li, Wang Lei

Journal of System Simulation

Abstract: Aircraft scheduling was studied, and an optimization model of aircraft assignment based on the objective function of maximize total profit was suggested. It considered its cost and benefits by combining fleet and aircraft. In the view of the feature of this model, the innovation of genetic algorithm chromosome was carried on, and these chromosomes formatted chromosome groups. The groups interior could cross over and mutate, and the probability of crossover and mutation could dynamically adjust in accordance with adaptive values to accelerate the convergence speed, the model was resolved fast in this way. In the process of simulation with …

Integrated Dynamic Equivalent Model Of Super Capacitor Energy Storage System, Xinran Li, Tingting Xu, Shaojie Tan, Xingting Cheng, Xiaojun Zeng

Journal of System Simulation

Abstract: As a high-power energy storage device, super capacitor (SC) is applied in micro-grid energy storage, secondary frequency regulation and peak load shifting in power system, and the research of which has become a hotspot. A second-order model of SC monomer suitable for the grid simulation was established, and the parameter identification using the charge and discharge experiment data under constant current and constant power modes was conducted based on genetic algorithm. A SC energy storage system has been set up in Simulink/Matlab based on the established second-order model of SC. The integrated dynamic equivalent model of SC energy storage …

Development Of A 3d Computational Vocal Fold Model Optimization Tool, Austin C. Vaterlaus

Theses and Dissertations

One of the primary objectives of voice research is to better understand the biomechanics of voice production and how changes in properties of the vocal folds (VFs) affect voice ability and quality. Synthetic VF models provide a way to observe how changes in geometry and material property affect voice biomechanics. This thesis seeks to evaluate an approach of using a genetic algorithm to design synthetic VF models in three ways: first, through the development of a computationally cost-effective 3D vocal fold model; second, by creating and optimizing a variation of this model; and third, by validating the approach. To reduce …

Research On Dynamic Flexible Job Shop Scheduling Problem For Energy Consumption, Chen Chao, Wang Yan, Dahu Yan, Zhicheng Ji

Journal of System Simulation

Abstract: In order to solve the problem of uneven load and energy consumption under disturbance, a flexible job shop scheduling model with average flow time and energy consumption was constructed. Aiming at the above model, a genetic and simulated annealing algorithm (GASA) was designed, which is based on the genetic algorithm and the simulated annealing algorithm. A new group of individuals were generated by genetic algorithm. And then the individual simulated the annealing process, in order to avoid falling into the local optimal. Aiming at the dynamic flexible job shop scheduling problem, the rolling window technique and GASA algorithm were …

Modeling And Simulation Of Mooring Force Prediction Based On Improved Ga-Bp Network, Shifeng Li, Zhanzhi Qiu

Journal of System Simulation

Abstract: According to the mooring security and early warning control requirement of the large open sea terminal, a ship mooring force prediction model based on genetic algorithm and BP network was studied. Environmental dynamic factors were considered and a model structure was determined by a weight statistics method; the learning method was improved by individual parent information and contemporary individual local gradient information; according to the improved model, a ship mooring force prediction method of the open sea terminal was proposed. The simulation results show that the performance of the prediction model has improved in the iteration number, …

Genetic Algorithm For Solving Multi-Objective Dynamic Flexible Job Shop Scheduling, Wang Chun, Zhang Ming, Zhicheng Ji, Wang Yan

Journal of System Simulation

Abstract: To solve the scheduling problem of mold workshop in a toy factory with dynamic and flexible features, a mathematical model was established by introducing virtual operation and virtual working hours. Based on the strategies of periodic scheduling combined with dynamic event scheduling as well as the rolling window scheduling operation technology, dynamic scheduling was transformed into several continuous static scheduling windows, under which multi-objective genetic algorithm was used to solve the model. The priority of operation scheduling was given in different dynamic events. In addition, the encoding and anti-encoding of chromosome's operation sequence were made based on the proposed …

Kinetic Insights Into The Lignocellulosic Biomass-Based Levulinic Acid Production By A Mechanistic Model, Emília Savioli Lopes, Elmer Ccopa Rivera, Julio César De Jesus Gariboti, Luis Henrique Zimmermann Feistel, João Vitor Dutra, Rubens Maciel Filho, Laura Plazas Tovar

Faculty Publications

© 2020, Springer Nature B.V. Abstract: In this work, a mechanistic model was developed to simulate the kinetics of the production of levulinic acid (LA) from sugarcane bagasse (SCB), rice husk (RH) and soybean straw (SS). The production of LA from those agro-industrial wastes followed the methodology of biorefining in three stages. Experimental data from the third stage (catalytic depolymerization of cellulose) obtained under a wide range of operating conditions were used to estimate the parameters of the model. An optimization procedure based on a genetic algorithm was used to determine the optimal parameter values. The prediction of the concentrations …

The Application Of Evolutionary Algorithms In Multi-Objective Design And Optimization Of Air Cooled Heatsinks, Younis Osama Abdelsalam, Sajad Alimohammadi, Tim Persoons

Articles

Genetic algorithms (GAs) are considered to be one of the main types of evolutionary algorithms (EAs) and are being increasingly used in various engineering design applications. To a large extent, plate-fin heatsinks are used in the thermal management of compact electronic equipment and data centers. The shape optimization of the heatsinks is not rigorously investigated during the design process of high power electronics. Any improvements in the effectiveness of the heatsinks impact the energy consumed by large-scale information communication technology (ICT) facilities including data centers and telecommunication systems and promote a more sustainable use of raw materials. This paper investigates …

Heuristic Approaches For Near-Optimal Placement Of Gps-Based Multi-Static Radar Receivers In American Coastal Waters, Brandon J. Hufstetler

Theses and Dissertations

Narcotics smuggling across the Caribbean Sea is a growing concern for the United States Coast Guard. One vector for this illicit trafficking is via small aircraft. This thesis proposes a multi-static radar architecture using the Global Positioning System (GPS) constellation as a transmission source to detect these aircraft as they transit a detection fence. The system developed in this thesis relies on the forward-scatter phenomenon in which a radar shadow is cast by a target as it crosses in front of a transmitter, creating a measurable difference in the signal amplitude at the receiver. This thesis first develops a mathematical …

Satellite Constellation Deployment And Management, Joseph Ryan Kopacz

Electronic Theses and Dissertations

This paper will review results and discuss a new method to address the deployment and management of a satellite constellation. The first two chapters will explorer the use of small satellites, and some of the advances in technology that have enabled small spacecraft to maintain modern performance requirements in incredibly small packages.

The third chapter will address the multiple-objective optimization problem for a global persistent coverage constellation of communications spacecraft in Low Earth Orbit. A genetic algorithm was implemented in MATLAB to explore the design space – 288 trillion possibilities – utilizing the Satellite Tool Kit (STK) software developers kit. …

A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale

Turkish Journal of Electrical Engineering and Computer Sciences

Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …

A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh

Turkish Journal of Electrical Engineering and Computer Sciences

One of the critical factors that make a search engine fast and accurate is a concise and duplicate free index. In order to remove duplicate and near-duplicate (DND) documents from the index, a search engine needs a swift and reliable DND text document detection system. Traditional approaches to this problem, such as brute force comparisons or simple hash-based algorithms, are not suitable as they are not scalable and are not capable of detecting near-duplicate documents effectively. In this paper, a new signature-based approach to text similarity detection is introduced, which is fast, scalable, and reliable and needs less storage space. …

Chemical Disease Relation Extraction Task Using Genetic Algorithm With Two Novelvoting Methods For Classifier Subset Selection, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş

Turkish Journal of Electrical Engineering and Computer Sciences

Biomedical relation extraction is an important preliminary step for knowledge discovery in the biomedical domain. This paper proposes a multiple classifier system (MCS) for the extraction of chemical-induced disease relations. A genetic algorithm (GA) is employed to select classifier ensembles from a pool of base classifiers. Moreover, the voting method used for combining the members of each of the ensembles is also selected during evolution in the GA framework. The performances of the MCSs are determined by the algorithms used for selecting the classifiers, the diversity among the selected classifiers, and the voting method used in the classifier combination. The …