In the traffic equilibrium problem, we introduce capacity constraints of arcs, extend Beckmann’s formula to include these constraints, and give an algorithm for traffic equilibrium flows with capacity constraints on ...In the traffic equilibrium problem, we introduce capacity constraints of arcs, extend Beckmann’s formula to include these constraints, and give an algorithm for traffic equilibrium flows with capacity constraints on arcs. Using an example, we illustrate the application of the algorithm and show that Beckmann’s formula is a sufficient condition only, not a necessary condition, for traffic equilibrium with capacity constraints of arcs.展开更多
In this paper, we propose an arc-search interior-point algorithm for convex quadratic programming with a wide neighborhood of the central path, which searches the optimizers along the ellipses that approximate the ent...In this paper, we propose an arc-search interior-point algorithm for convex quadratic programming with a wide neighborhood of the central path, which searches the optimizers along the ellipses that approximate the entire central path. The favorable polynomial complexity bound of the algorithm is obtained, namely O（nlog（（ x^0）~TS^0/ε）） which is as good as the linear programming analogue. Finally, the numerical experiments show that the proposed algorithm is efficient.展开更多
This paper is to represent new algorithms to predict process parameters on top-bead width in robotic gas metal arc（GMA） welding process.The models have been developed：linear, curvilinear and intelligent model based...This paper is to represent new algorithms to predict process parameters on top-bead width in robotic gas metal arc（GMA） welding process.The models have been developed：linear, curvilinear and intelligent model based on full factorial design with two replications.Regression analysis was employed for optimization of the coefficients of linear and curvilinear models, while genetic algorithm（GA） was utilized to estimate the coefficients of an intelligent model.Not only the fitting of these models were checked and compared by using a variance test（ANOVA）, but also the prediction on top-bead width using the developed models were carried out based on the additional experiments.The developed models were employed to investigate the characteristic between process parameters and top-bead width.Resulting solutions and graphical representation showed that the intelligent model developed can be employed for prediction of bead geometry in GMA welding process.展开更多
AISI 304L is an austenitic Chromium-Nickel stainless steel offering the optimum combination of corrosion resistance, strength and ductility. These attributes make it a favorite for many mechanical components. The pape...AISI 304L is an austenitic Chromium-Nickel stainless steel offering the optimum combination of corrosion resistance, strength and ductility. These attributes make it a favorite for many mechanical components. The paper focuses on developing mathematical models to predict grain size and hardness of pulsed current micro plasma arc welded AISI 304L joints. Four factors, five level, central composite rotatable design matrix is used to optimize the number of experiments. The mathematical models have been developed by Response Surface Method (RSM) and its adequacy is checked by Analysis of Variance (ANOVA) technique. By using the developed mathematical models, grain size and hardness of the weld joints can be predicted with 99% confidence level. The developed mathematical models have been optimized using Hooke and Jeeves algorithm to minimize grain size and maximize the hardness.展开更多
The feedback vertex set (FVS) problem is to find the set of vertices of minimum cardinality whose removal renders the graph acyclic. The FVS problem has applications in several areas such as combinatorial circuit desi...The feedback vertex set (FVS) problem is to find the set of vertices of minimum cardinality whose removal renders the graph acyclic. The FVS problem has applications in several areas such as combinatorial circuit design, synchronous systems, computer systems, and very-large-scale integration (VLSI) circuits. The FVS problem is known to be NP-hard for simple graphs, but polynomi-al-time algorithms have been found for special classes of graphs. The intersection graph of a collection of arcs on a circle is called a circular-arc graph. A normal Helly circular-arc graph is a proper subclass of the set of circular-arc graphs. In this paper, we present an algorithm that takes time to solve the FVS problem in a normal Helly circular-arc graph with n vertices and m edges.展开更多
By using alternating current plasma arc welding,the influences were studied of such parameters as welding curent,arc voltage,welding speed,wire feed rate,and magnitude of ion gas flow on front melting width,wdle rei...By using alternating current plasma arc welding,the influences were studied of such parameters as welding curent,arc voltage,welding speed,wire feed rate,and magnitude of ion gas flow on front melting width,wdle reinforcement,and back melting width of LF6 aluminum alloy.Model of the formation of welding seam in alternating current plasma arc welding of aluminum was set up with the method of artificial neural neural network - BP algorithm. Qyakuty of formation was consequently predicted and evaluated.The experimental result shows that,compared with other modeling methods,artificial network model can be used to more accurately predict formation of weld,and to guide the production practice.展开更多
Submerged arc welding(SAW), owing to its high deposition rate and high welding quality, is widely used in the fabrication of pressure vessel, marine vessel, pipelines and offshore structures. However, selection of an ...Submerged arc welding(SAW), owing to its high deposition rate and high welding quality, is widely used in the fabrication of pressure vessel, marine vessel, pipelines and offshore structures. However, selection of an optimum combination of welding parameters is critical in achieving high weld quality and productivity. In this work, initially, the SAW experiments were performed using fractional factorial design to analyze the effect of direct and indirect input parameters, namely, welding voltage, wire feed rate,welding speed, nozzle to plate distance, flux condition, and plate thickness on weld bead geometrical responses viz. bead width, reinforcement, and penetration. The bead on plate technique was used to deposit weld metal on AISI 1023 steel plates. The effect of SAW input parameters on response variables were analyzed using main and interaction effects. The linear regression was used to develop the mathematical models for the response variable. Then, the multi-objective optimization of input parameters was carried out using desirability approach, genetic algorithm and Jaya algorithm. The Jaya algorithm offered better optimization results as compared to desirability approach, genetic algorithm.展开更多
Plasma surface hardening process was performed to improve the performance of the AISI 1045 carbon steel.Experiments were carried out to characterize the hardening qualities.A predicting and optimizing model using gene...Plasma surface hardening process was performed to improve the performance of the AISI 1045 carbon steel.Experiments were carried out to characterize the hardening qualities.A predicting and optimizing model using genetic algorithm-back propagation neural network（GA-BP） was developed based on the experimental results.The non-linear relationship between properties of hardening layers and process parameters was established.The results show that the GA-BP predicting model is reliable since prediction results are in rather good agreement with measured results.The optimal properties of the hardened layer were deduced from GA.And through multi optimizations,the optimum comprehensive performances of the hardened layer were as follows：plasma arc current is 90 A,hardening speed is 2.2 m/min,plasma gas flow rate is 6.0 L/min and hardening distance is 4.3 mm.It concludes that GA-BP mode developed in this study provides a promising method for plasma hardening parameters prediction and optimization.展开更多
Directed networks such as gene regulation networks and neural networks are connected by arcs（directed links）. The nodes in a directed network are often strongly interwound by a huge number of directed cycles, which ...Directed networks such as gene regulation networks and neural networks are connected by arcs（directed links）. The nodes in a directed network are often strongly interwound by a huge number of directed cycles, which leads to complex information-processing dynamics in the network and makes it highly challenging to infer the intrinsic direction of information flow. In this theoretical paper, based on the principle of minimum-feedback, we explore the node hierarchy of directed networks and distinguish feedforward and feedback arcs. Nearly optimal node hierarchy solutions, which minimize the number of feedback arcs from lower-level nodes to higher-level nodes, are constructed by belief-propagation and simulated-annealing methods. For real-world networks, we quantify the extent of feedback scarcity by comparison with the ensemble of direction-randomized networks and identify the most important feedback arcs. Our methods are also useful for visualizing directed networks.展开更多
Arc sensing plays a significant role in the control and monitoring of welding quality for aluminum alloy pulsed gas touch argon welding(GTAW). A method for online quality monitoring based on adaptive boosting algorith...Arc sensing plays a significant role in the control and monitoring of welding quality for aluminum alloy pulsed gas touch argon welding(GTAW). A method for online quality monitoring based on adaptive boosting algorithm is proposed through the analysis of acquired arc voltage signal. Two feature extraction algorithms were developed in time domain and frequency domain respectively to extract six statistic characteristic parameters before removing the pulse interference using the wavelet packet transform(WPT), based on which the Adaboost classification model is successfully established to evaluate and classify the welding quality into two classes and the classified accuracy of the model is as high as 98.81%. The Adaboost algorithm has been verified to be feasible in the online evaluation of welding quality.展开更多
This paper presents a new application of a genetic-fuzzy control system which controls the input energy to a three phase electric arc furnace. Graphite electrodes are used to convert electrical energy into heat via ph...This paper presents a new application of a genetic-fuzzy control system which controls the input energy to a three phase electric arc furnace. Graphite electrodes are used to convert electrical energy into heat via phase electric arcs. Con-stant arc length is desirable as it implies steady energy transfer from the graphite electrodes to the metallic charge in the furnace bath. With the charge level constantly changing, the electrodes must be able to adjust for the arc length to remain constant. A fuzzy PI controller tuned with genetic algorithms has been developed to be responsible for the ver-tical adjustment of the electrode tip displacement according to specified set-points to ensure that the arc lengths remain as constant as possible. The simulation results show that the system performances are satisfactory using the proposed method.展开更多
文摘In the traffic equilibrium problem, we introduce capacity constraints of arcs, extend Beckmann’s formula to include these constraints, and give an algorithm for traffic equilibrium flows with capacity constraints on arcs. Using an example, we illustrate the application of the algorithm and show that Beckmann’s formula is a sufficient condition only, not a necessary condition, for traffic equilibrium with capacity constraints of arcs.
基金Supported by the National Natural Science Foundation of China(71471102)
文摘In this paper, we propose an arc-search interior-point algorithm for convex quadratic programming with a wide neighborhood of the central path, which searches the optimizers along the ellipses that approximate the entire central path. The favorable polynomial complexity bound of the algorithm is obtained, namely O（nlog（（ x^0）~TS^0/ε）） which is as good as the linear programming analogue. Finally, the numerical experiments show that the proposed algorithm is efficient.
基金supported by the 2006 research funds from Mokpo National University
文摘This paper is to represent new algorithms to predict process parameters on top-bead width in robotic gas metal arc（GMA） welding process.The models have been developed：linear, curvilinear and intelligent model based on full factorial design with two replications.Regression analysis was employed for optimization of the coefficients of linear and curvilinear models, while genetic algorithm（GA） was utilized to estimate the coefficients of an intelligent model.Not only the fitting of these models were checked and compared by using a variance test（ANOVA）, but also the prediction on top-bead width using the developed models were carried out based on the additional experiments.The developed models were employed to investigate the characteristic between process parameters and top-bead width.Resulting solutions and graphical representation showed that the intelligent model developed can be employed for prediction of bead geometry in GMA welding process.
文摘AISI 304L is an austenitic Chromium-Nickel stainless steel offering the optimum combination of corrosion resistance, strength and ductility. These attributes make it a favorite for many mechanical components. The paper focuses on developing mathematical models to predict grain size and hardness of pulsed current micro plasma arc welded AISI 304L joints. Four factors, five level, central composite rotatable design matrix is used to optimize the number of experiments. The mathematical models have been developed by Response Surface Method (RSM) and its adequacy is checked by Analysis of Variance (ANOVA) technique. By using the developed mathematical models, grain size and hardness of the weld joints can be predicted with 99% confidence level. The developed mathematical models have been optimized using Hooke and Jeeves algorithm to minimize grain size and maximize the hardness.
文摘The feedback vertex set (FVS) problem is to find the set of vertices of minimum cardinality whose removal renders the graph acyclic. The FVS problem has applications in several areas such as combinatorial circuit design, synchronous systems, computer systems, and very-large-scale integration (VLSI) circuits. The FVS problem is known to be NP-hard for simple graphs, but polynomi-al-time algorithms have been found for special classes of graphs. The intersection graph of a collection of arcs on a circle is called a circular-arc graph. A normal Helly circular-arc graph is a proper subclass of the set of circular-arc graphs. In this paper, we present an algorithm that takes time to solve the FVS problem in a normal Helly circular-arc graph with n vertices and m edges.
文摘By using alternating current plasma arc welding,the influences were studied of such parameters as welding curent,arc voltage,welding speed,wire feed rate,and magnitude of ion gas flow on front melting width,wdle reinforcement,and back melting width of LF6 aluminum alloy.Model of the formation of welding seam in alternating current plasma arc welding of aluminum was set up with the method of artificial neural neural network - BP algorithm. Qyakuty of formation was consequently predicted and evaluated.The experimental result shows that,compared with other modeling methods,artificial network model can be used to more accurately predict formation of weld,and to guide the production practice.
文摘Submerged arc welding(SAW), owing to its high deposition rate and high welding quality, is widely used in the fabrication of pressure vessel, marine vessel, pipelines and offshore structures. However, selection of an optimum combination of welding parameters is critical in achieving high weld quality and productivity. In this work, initially, the SAW experiments were performed using fractional factorial design to analyze the effect of direct and indirect input parameters, namely, welding voltage, wire feed rate,welding speed, nozzle to plate distance, flux condition, and plate thickness on weld bead geometrical responses viz. bead width, reinforcement, and penetration. The bead on plate technique was used to deposit weld metal on AISI 1023 steel plates. The effect of SAW input parameters on response variables were analyzed using main and interaction effects. The linear regression was used to develop the mathematical models for the response variable. Then, the multi-objective optimization of input parameters was carried out using desirability approach, genetic algorithm and Jaya algorithm. The Jaya algorithm offered better optimization results as compared to desirability approach, genetic algorithm.
文摘Plasma surface hardening process was performed to improve the performance of the AISI 1045 carbon steel.Experiments were carried out to characterize the hardening qualities.A predicting and optimizing model using genetic algorithm-back propagation neural network（GA-BP） was developed based on the experimental results.The non-linear relationship between properties of hardening layers and process parameters was established.The results show that the GA-BP predicting model is reliable since prediction results are in rather good agreement with measured results.The optimal properties of the hardened layer were deduced from GA.And through multi optimizations,the optimum comprehensive performances of the hardened layer were as follows：plasma arc current is 90 A,hardening speed is 2.2 m/min,plasma gas flow rate is 6.0 L/min and hardening distance is 4.3 mm.It concludes that GA-BP mode developed in this study provides a promising method for plasma hardening parameters prediction and optimization.
基金Project by the National Basic Research Program of China(Grant No.2013CB932804)the National Natural Science Foundations of China(Grant Nos.11121403 and 11225526)support by Fondazione CRT under project SIBYL,initiative "La Ricerca dei Talenti"
文摘Directed networks such as gene regulation networks and neural networks are connected by arcs（directed links）. The nodes in a directed network are often strongly interwound by a huge number of directed cycles, which leads to complex information-processing dynamics in the network and makes it highly challenging to infer the intrinsic direction of information flow. In this theoretical paper, based on the principle of minimum-feedback, we explore the node hierarchy of directed networks and distinguish feedforward and feedback arcs. Nearly optimal node hierarchy solutions, which minimize the number of feedback arcs from lower-level nodes to higher-level nodes, are constructed by belief-propagation and simulated-annealing methods. For real-world networks, we quantify the extent of feedback scarcity by comparison with the ensemble of direction-randomized networks and identify the most important feedback arcs. Our methods are also useful for visualizing directed networks.
基金the National Natural Science Foundation of China(No.51275301)
文摘Arc sensing plays a significant role in the control and monitoring of welding quality for aluminum alloy pulsed gas touch argon welding(GTAW). A method for online quality monitoring based on adaptive boosting algorithm is proposed through the analysis of acquired arc voltage signal. Two feature extraction algorithms were developed in time domain and frequency domain respectively to extract six statistic characteristic parameters before removing the pulse interference using the wavelet packet transform(WPT), based on which the Adaboost classification model is successfully established to evaluate and classify the welding quality into two classes and the classified accuracy of the model is as high as 98.81%. The Adaboost algorithm has been verified to be feasible in the online evaluation of welding quality.
文摘This paper presents a new application of a genetic-fuzzy control system which controls the input energy to a three phase electric arc furnace. Graphite electrodes are used to convert electrical energy into heat via phase electric arcs. Con-stant arc length is desirable as it implies steady energy transfer from the graphite electrodes to the metallic charge in the furnace bath. With the charge level constantly changing, the electrodes must be able to adjust for the arc length to remain constant. A fuzzy PI controller tuned with genetic algorithms has been developed to be responsible for the ver-tical adjustment of the electrode tip displacement according to specified set-points to ensure that the arc lengths remain as constant as possible. The simulation results show that the system performances are satisfactory using the proposed method.
