In this paper,two numerical methods are proposed for solving distributed-order fractional Bagley-Torvik equation.This equation is used in modeling the motion of a rigid plate immersed in a Newtonian fluid with respect...In this paper,two numerical methods are proposed for solving distributed-order fractional Bagley-Torvik equation.This equation is used in modeling the motion of a rigid plate immersed in a Newtonian fluid with respect to the nonnegative density function.Using the composite Boole's rule the distributedorder Bagley-Torvik equation is approximated by a multi-term time-fractional equation,which is then solved by the GrunwaldLetnikov method(GLM)and the fractional differential transform method(FDTM).Finally,we compared our results with the exact results of some cases and show the excellent agreement between the approximate result and the exact solution.展开更多
This article presents very original and relatively brief or very brief proofs about of two famous problems: 1) Are there any odd perfect numbers? and 2) “Fermat’s last theorem: A new proof of theorem and its general...This article presents very original and relatively brief or very brief proofs about of two famous problems: 1) Are there any odd perfect numbers? and 2) “Fermat’s last theorem: A new proof of theorem and its generalization”. They are achieved with elementary mathematics. This is why these proofs can be easily understood by any mathematician or anyone who knows basic mathematics. Note that, in both problems, proof by contradiction was used as a method of proof. The first of the two problems to date has not been resolved. Its proof is completely original and was not based on the work of other researchers. On the contrary, it was based on a simple observation that all natural divisors of a positive integer appear in pairs. The aim of the first work is to solve one of the unsolved, for many years, problems of the mathematics which belong to the field of number theory. I believe that if the present proof is recognized by the mathematical community, it may signal a different way of solving unsolved problems. For the second problem, it is very important the fact that it is generalized to an arbitrarily large number of variables. This generalization is essentially a new theorem in the field of the number theory. To the classical problem, two solutions are given, which are presented in the chronological order in which they were achieved. Note that the second solution is very short and does not exceed one and a half pages. This leads me to believe that Fermat, as a great mathematician was not lying and that he had probably solved the problem, as he stated in his historic its letter, with a correspondingly brief solution. To win the bet on the question of whether Fermat was telling truth or lying, go immediately to the end of this article before the General Conclusions.展开更多
The relevance of studying the storage coefficient variable brings with it the updating of this value in the hydraulic characteristics as part of the hydrogeological parameters applied to each country, where recommende...The relevance of studying the storage coefficient variable brings with it the updating of this value in the hydraulic characteristics as part of the hydrogeological parameters applied to each country, where recommended values for the storage coefficient to be used in hydrogeological studies are presented. And the application of a methodology adapted to the conditions of each country, is done under current conditions resulting in reference values. For this research work, an adequate methodology was sought for calculating the storage coefficient with a natural logarithm (LN) arrangement. To achieve this, first, the variables that affect the storage coefficient were identified, then the model was described with the natural logarithm (LN) arrangement, and as a third point the storage coefficient was calculated. In conclusion, in points 1 and 2 it was possible to calculate the storage coefficient from the Natural Logarithm arrangement model, with a correlation equal to R<sup>2</sup> = 0.99, and R<sup>2</sup> = 0.97 respectively, indicating that this method can be applied as long as there is free aquifer conditions and that manipulation of data alteration is not frequent.展开更多
For this research work, an adequate methodology was sought for the calculation of the runoff coefficient with the Tirado arrangement. To achieve this, first, the variables that affect the runoff coefficient were ident...For this research work, an adequate methodology was sought for the calculation of the runoff coefficient with the Tirado arrangement. To achieve this, first, the variables that affect the runoff coefficient were identified, then the model was described with the Tirado arrangement, and as a third part for the calculation of the runoff coefficient, the Tirado model is proposed. From the theory for the calculation of the runoff coefficient, the equation of the weighted coefficients and the expression of Nadal were manipulated, resulting in the following relationship , considering this as the expression for the arrangement Tirado. The expression is tested with different intensities, the magnitudes correspond to 150, 200, 250 and 300 mm/hrs, resulting in runoff coefficient 0.82, 0.87, 0.89, 0.91 respectively. This means that, the higher the intensity, the runoff coefficient will be higher, logically the characteristics of the basin affect that this coefficient has variation in the space studied.展开更多
In this work,we combined the model based reinforcement learning(MBRL)and model free reinforcement learning(MFRL)to stabilize a biped robot(NAO robot)on a rotating platform,where the angular velocity of the platform is...In this work,we combined the model based reinforcement learning(MBRL)and model free reinforcement learning(MFRL)to stabilize a biped robot(NAO robot)on a rotating platform,where the angular velocity of the platform is unknown for the proposed learning algorithm and treated as the external disturbance.Nonparametric Gaussian processes normally require a large number of training data points to deal with the discontinuity of the estimated model.Although some improved method such as probabilistic inference for learning control(PILCO)does not require an explicit global model as the actions are obtained by directly searching the policy space,the overfitting and lack of model complexity may still result in a large deviation between the prediction and the real system.Besides,none of these approaches consider the data error and measurement noise during the training process and test process,respectively.We propose a hierarchical Gaussian processes(GP)models,containing two layers of independent GPs,where the physically continuous probability transition model of the robot is obtained.Due to the physically continuous estimation,the algorithm overcomes the overfitting problem with a guaranteed model complexity,and the number of training data is also reduced.The policy for any given initial state is generated automatically by minimizing the expected cost according to the predefined cost function and the obtained probability distribution of the state.Furthermore,a novel Q(λ)based MFRL method scheme is employed to improve the policy.Simulation results show that the proposed RL algorithm is able to balance NAO robot on a rotating platform,and it is capable of adapting to the platform with varying angular velocity.展开更多
Prof. Ren Fuji received his B.E. and M.E. degrees from Beijing University of Posts and Telecommunications, Beijing, China, in 1982 and 1985, respectively. He received his Ph.D. degree in 1991 from Hokkaido University,...Prof. Ren Fuji received his B.E. and M.E. degrees from Beijing University of Posts and Telecommunications, Beijing, China, in 1982 and 1985, respectively. He received his Ph.D. degree in 1991 from Hokkaido University, Japan. He is a professor in the Faculty of Engineering of the University of Tokushima, Japan. His research interests include natural language processing, artificial intelligence, language understanding and communication, and affective computing. He is a member of IEICE, CAAI, IEEJ, IPSJ, JSAI, AAMT, and IEEE. He is a fellow of the Japan Federation of Engineering Societies. He is the president of the International Advanced Information Institute and Vice Presidentof Chinese Association of Artificial Intelligence.展开更多
A performance evaluation of sound recognition techniques in recognizing some spoken Arabic words, namely digits from zero to nine, is proposed. One of the main characteristics of aU Arabic digits is polysyllabic words...A performance evaluation of sound recognition techniques in recognizing some spoken Arabic words, namely digits from zero to nine, is proposed. One of the main characteristics of aU Arabic digits is polysyllabic words except for zero. The performance analysis is based on different features of phonetic isolated Arabic digits. The main aim of this paper is to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on three recognition features： the Yule-Walker spectrum features, the Walsh spectrum features, and the Mel frequency Cepstral coefficients （MFCC） features. The MFCC based recognition system achieves the best average correct recognition. On the other hand, the Yule-Walker based recognition system achieves the worst average correct recognition.展开更多
The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimiz...The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.展开更多
Prediction methods have garnered significant attention in intelligent decision-making.Most existing approaches to predicting crude oil prices prioritize accuracy and stability while providing precise prediction interv...Prediction methods have garnered significant attention in intelligent decision-making.Most existing approaches to predicting crude oil prices prioritize accuracy and stability while providing precise prediction intervals that can offer valuable insights.Thus far,we introduced a novel hybrid model to forecast future crude oil prices.Our approach leverages the variational mode decomposition(VMD)to simplify the complexity of the original time series,yielding a set of subseries.These subseries are then modeled using a deep neural network architecture called a gated recurrent unit(GRU).To address the prediction uncertainty,we employed the pinball loss function rather than the mean square error to guide the proposed VMD-GRU.This adaptation extends the traditional GRUbased point forecasting to probabilistic forecasting by estimating quantiles.We evaluated our proposed model on a well-established crude oil price series by conducting both single-and multi-step-ahead forecasting analyses.Our findings underscore the efficacy of the combined model,demonstrating its superior predictive performance compared to benchmark models.展开更多
A gravitational search algorithm(GSA)uses gravitational force among individuals to evolve population.Though GSA is an effective population-based algorithm,it exhibits low search performance and premature convergence.T...A gravitational search algorithm(GSA)uses gravitational force among individuals to evolve population.Though GSA is an effective population-based algorithm,it exhibits low search performance and premature convergence.To ameliorate these issues,this work proposes a multi-layered GSA called MLGSA.Inspired by the two-layered structure of GSA,four layers consisting of population,iteration-best,personal-best and global-best layers are constructed.Hierarchical interactions among four layers are dynamically implemented in different search stages to greatly improve both exploration and exploitation abilities of population.Performance comparison between MLGSA and nine existing GSA variants on twenty-nine CEC2017 test functions with low,medium and high dimensions demonstrates that MLGSA is the most competitive one.It is also compared with four particle swarm optimization variants to verify its excellent performance.Moreover,the analysis of hierarchical interactions is discussed to illustrate the influence of a complete hierarchy on its performance.The relationship between its population diversity and fitness diversity is analyzed to clarify its search performance.Its computational complexity is given to show its efficiency.Finally,it is applied to twenty-two CEC2011 real-world optimization problems to show its practicality.展开更多
Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that red...Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that reduces the power outputs of wind turbines located in downstream.Wind farm layout optimization(WFLO)aims to reduce the wake effect for maximizing the power outputs of the wind farm.Nevertheless,the wake effect among wind turbines increases significantly as the number of wind turbines increases in the wind farm,which severely affect power conversion efficiency.Conventional heuristic algorithms suffer from issues of low solution quality and local optimum for large-scale WFLO under complex wind scenarios.Thus,a chaotic local search-based genetic learning particle swarm optimizer(CGPSO)is proposed to optimize large-scale WFLO problems.CGPSO is tested on four larger-scale wind farms under four complex wind scenarios and compares with eight state-of-the-art algorithms.The experiment results indicate that CGPSO significantly outperforms its competitors in terms of performance,stability,and robustness.To be specific,a success and failure memories-based selection is proposed to choose a chaotic map for chaotic search local.It improves the solution quality.The parameter and search pattern of chaotic local search are also analyzed for WFLO problems.展开更多
In this paper,a global optimum-based search strategy is proposed to alleviate the situation that the differential evolution(DE)usually sticks into a stagnation,especially on complex problems.It aims to reconstruct the...In this paper,a global optimum-based search strategy is proposed to alleviate the situation that the differential evolution(DE)usually sticks into a stagnation,especially on complex problems.It aims to reconstruct the balance between exploration and exploitation,and improve the search efficiency and solution quality of DE.The proposed method is activated by recording the number of recently consecutive unsuccessful global optimum updates.It takes the feedback from the global optimum,which makes the search strategy not only refine the current solution quality,but also have a change to find other promising space with better individuals.This search strategy is incorporated with various DE mutation strategies and DE variations.The experimental results indicate that the proposed method has remarkable performance in enhancing search efficiency and improving solution quality.展开更多
In this paper,we elaborate on residual-driven Fuzzy C-Means(FCM)for image segmentation,which is the first approach that realizes accurate residual(noise/outliers)estimation and enables noise-free image to participate ...In this paper,we elaborate on residual-driven Fuzzy C-Means(FCM)for image segmentation,which is the first approach that realizes accurate residual(noise/outliers)estimation and enables noise-free image to participate in clustering.We propose a residual-driven FCM framework by integrating into FCM a residual-related regularization term derived from the distribution characteristic of different types of noise.Built on this framework,a weighted?2-norm regularization term is presented by weighting mixed noise distribution,thus resulting in a universal residual-driven FCM algorithm in presence of mixed or unknown noise.Besides,with the constraint of spatial information,the residual estimation becomes more reliable than that only considering an observed image itself.Supporting experiments on synthetic,medical,and real-world images are conducted.The results demonstrate the superior effectiveness and efficiency of the proposed algorithm over its peers.展开更多
The multitrip pickup and delivery problem with time windows and manpower planning(MTPDPTW-MP)determines a set of ambulance routes and finds staff assignment for a hospital. It involves different stakeholders with dive...The multitrip pickup and delivery problem with time windows and manpower planning(MTPDPTW-MP)determines a set of ambulance routes and finds staff assignment for a hospital. It involves different stakeholders with diverse interests and objectives. This study firstly introduces a multiobjective MTPDPTW-MP(MO-MTPDPTWMP) with three objectives to better describe the real-world scenario. A multiobjective iterated local search algorithm with adaptive neighborhood selection(MOILS-ANS) is proposed to solve the problem. MOILS-ANS can generate a diverse set of alternative solutions for decision makers to meet their requirements. To better explore the search space, problem-specific neighborhood structures and an adaptive neighborhood selection strategy are carefully designed in MOILS-ANS. Experimental results show that the proposed MOILS-ANS significantly outperforms the other two multiobjective algorithms. Besides, the nature of objective functions and the properties of the problem are analyzed. Finally, the proposed MOILS-ANS is compared with the previous single-objective algorithm and the benefits of multiobjective optimization are discussed.展开更多
Dear Editor,This letter presents a novel segmentation approach that leverages dendritic neurons to tackle the challenges of medical imaging segmentation.In this study,we enhance the segmentation accuracy based on a Se...Dear Editor,This letter presents a novel segmentation approach that leverages dendritic neurons to tackle the challenges of medical imaging segmentation.In this study,we enhance the segmentation accuracy based on a SegNet variant including an encoder-decoder structure,an upsampling index,and a deep supervision method.Furthermore,we introduce a dendritic neuron-based convolutional block to enable nonlinear feature mapping,thereby further improving the effectiveness of our approach.展开更多
Dear Editor, This letter is concerned with the evolution strategy for addressing multi-objective feature selection problems in classification. Previous methods suffer from limitations such as being trapped in local op...Dear Editor, This letter is concerned with the evolution strategy for addressing multi-objective feature selection problems in classification. Previous methods suffer from limitations such as being trapped in local optima and lacking stability. To overcome them, we propose a novel eliteguided mechanism based on information theory. Firstly, an elite solution is generated through a dimension reduction strategy and incorporated to the initialization population.展开更多
Ozone is a green house gas. Ozone absorption cross sections have been reported with discrepancies and inconsistencies. In this paper, simultaneous effects of the optical path length and temperature variations on ozone...Ozone is a green house gas. Ozone absorption cross sections have been reported with discrepancies and inconsistencies. In this paper, simultaneous effects of the optical path length and temperature variations on ozone gas absorption cross sections are investigated at different wavelengths. HITRAN 2012, the latest available line list on spectralcalc.com simulator, is used in this study to simulate ozone gas absorption cross sections in relation to the simultaneous effects of the optical path length and temperature at the wavelengths of 603 nm and 575 nm. Results obtained for gas cells with the optical path length from 10 cm to 120 cm show that the decrease in temperatures from 313 K to 103 K results in the increase in ozone gas absorption cross sections. At wavelengths of 603 nm and 575 nm, the percentage increase of ozone gas absorption cross sections is 1.22% and 0.71%, respectively. Results obtained in this study show that in the visible spectrum, at constant pressure, ozone gas absorption cross sections are dependent on the temperature and wavelength but do not depend on the optical path length. Analysis in this work addresses discrepancies in ozone gas absorption cross sections in relation to the temperature in the visible spectrum; thus, the results can be applied to get optimal configuration of high accuracy ozone gas sensors.展开更多
A permanent magnet linear synchronous motor （PMLSM） for a high temperature superconducting （HTS） maglev system has been studied, including the motor structure, control strategy, and analysis techniques. Finite ele...A permanent magnet linear synchronous motor （PMLSM） for a high temperature superconducting （HTS） maglev system has been studied, including the motor structure, control strategy, and analysis techniques. Finite element analysis （FEA） of magnetic field is conducted to accurately calculate major motor parameters. Equivalent electrical circuit is used to predict the drive＇s steady-state characteristics, and a phase variable model is applied to predict the dynamic performance. Preliminary experiment with a prototype has been made to verify the theoretical analysis and the HTS-PM synchronous driving technology.展开更多
Demolition cementitious waste poses significant environmental challenges at the end of its lifecycle.To address this,fly ash(FA),a highly leachable material and a supplementary cementitious material,was combined with ...Demolition cementitious waste poses significant environmental challenges at the end of its lifecycle.To address this,fly ash(FA),a highly leachable material and a supplementary cementitious material,was combined with biochar(BC)to produce eco-friendly mortar bricks with reduced carbon emissions and contaminant leaching.BC was incorporated at 2%,4%,and 6%by weight,and the resulting blocks achieved compressive strengths of 8-12 MPa after 28 days,meeting Eurocode 6 standards for use in harsh conditions.Leaching tests under synthetic precipitation showed reductions in Al,Se,Ba,and Cr concentrations by 72%,48%,58%,and 53%,respectively,with 6%BC.While Al remained above drinking water limits,Cr levels dropped below limits when BC exceeded 4%.Leaching followed typical pH-dependent behaviour:Al exhibited an amphoteric trend,and Cr showed an oxyanionic trend,with minimal leaching at neutral pH.This study highlights the role of BC in reducing leaching potential in cementitious composites and provides critical data for geochemical modelling in sustainable demolition waste management systems.展开更多
This study investigated the performances of a new type of precast beam-column joint subjected to earthquake and impact loads.For sustainability and durability considerations,new materials such as corrosion-resistant f...This study investigated the performances of a new type of precast beam-column joint subjected to earthquake and impact loads.For sustainability and durability considerations,new materials such as corrosion-resistant fibre reinforced polymer(FRP)bolts and reinforcements,fibre reinforced concrete(FRC),and geopolymer concrete(GPC)were used to construct the joint.To examine the resilience,durability,sustainability,and multi-hazard resistance capacities,both cyclic and pendulum impact tests were carried out.The experimental results demonstrated that the proposed precast joints had the comparable or even better performances as compared with the traditional monolithic joints under cyclic and impact loads.Numerical simulations using ABAQUS were also adopted to determine the optimal values of the concrete-end-plate(CEP)thickness for the proposed dry joints and to further quantify other response parameters which could not be obtained during the test,e.g.,stress distribution,energy absorption,and stress contours.Discussion on the influences of various parameters on joint performances under different loading conditions was also presented in this study.展开更多
文摘In this paper,two numerical methods are proposed for solving distributed-order fractional Bagley-Torvik equation.This equation is used in modeling the motion of a rigid plate immersed in a Newtonian fluid with respect to the nonnegative density function.Using the composite Boole's rule the distributedorder Bagley-Torvik equation is approximated by a multi-term time-fractional equation,which is then solved by the GrunwaldLetnikov method(GLM)and the fractional differential transform method(FDTM).Finally,we compared our results with the exact results of some cases and show the excellent agreement between the approximate result and the exact solution.
文摘This article presents very original and relatively brief or very brief proofs about of two famous problems: 1) Are there any odd perfect numbers? and 2) “Fermat’s last theorem: A new proof of theorem and its generalization”. They are achieved with elementary mathematics. This is why these proofs can be easily understood by any mathematician or anyone who knows basic mathematics. Note that, in both problems, proof by contradiction was used as a method of proof. The first of the two problems to date has not been resolved. Its proof is completely original and was not based on the work of other researchers. On the contrary, it was based on a simple observation that all natural divisors of a positive integer appear in pairs. The aim of the first work is to solve one of the unsolved, for many years, problems of the mathematics which belong to the field of number theory. I believe that if the present proof is recognized by the mathematical community, it may signal a different way of solving unsolved problems. For the second problem, it is very important the fact that it is generalized to an arbitrarily large number of variables. This generalization is essentially a new theorem in the field of the number theory. To the classical problem, two solutions are given, which are presented in the chronological order in which they were achieved. Note that the second solution is very short and does not exceed one and a half pages. This leads me to believe that Fermat, as a great mathematician was not lying and that he had probably solved the problem, as he stated in his historic its letter, with a correspondingly brief solution. To win the bet on the question of whether Fermat was telling truth or lying, go immediately to the end of this article before the General Conclusions.
文摘The relevance of studying the storage coefficient variable brings with it the updating of this value in the hydraulic characteristics as part of the hydrogeological parameters applied to each country, where recommended values for the storage coefficient to be used in hydrogeological studies are presented. And the application of a methodology adapted to the conditions of each country, is done under current conditions resulting in reference values. For this research work, an adequate methodology was sought for calculating the storage coefficient with a natural logarithm (LN) arrangement. To achieve this, first, the variables that affect the storage coefficient were identified, then the model was described with the natural logarithm (LN) arrangement, and as a third point the storage coefficient was calculated. In conclusion, in points 1 and 2 it was possible to calculate the storage coefficient from the Natural Logarithm arrangement model, with a correlation equal to R<sup>2</sup> = 0.99, and R<sup>2</sup> = 0.97 respectively, indicating that this method can be applied as long as there is free aquifer conditions and that manipulation of data alteration is not frequent.
文摘For this research work, an adequate methodology was sought for the calculation of the runoff coefficient with the Tirado arrangement. To achieve this, first, the variables that affect the runoff coefficient were identified, then the model was described with the Tirado arrangement, and as a third part for the calculation of the runoff coefficient, the Tirado model is proposed. From the theory for the calculation of the runoff coefficient, the equation of the weighted coefficients and the expression of Nadal were manipulated, resulting in the following relationship , considering this as the expression for the arrangement Tirado. The expression is tested with different intensities, the magnitudes correspond to 150, 200, 250 and 300 mm/hrs, resulting in runoff coefficient 0.82, 0.87, 0.89, 0.91 respectively. This means that, the higher the intensity, the runoff coefficient will be higher, logically the characteristics of the basin affect that this coefficient has variation in the space studied.
文摘In this work,we combined the model based reinforcement learning(MBRL)and model free reinforcement learning(MFRL)to stabilize a biped robot(NAO robot)on a rotating platform,where the angular velocity of the platform is unknown for the proposed learning algorithm and treated as the external disturbance.Nonparametric Gaussian processes normally require a large number of training data points to deal with the discontinuity of the estimated model.Although some improved method such as probabilistic inference for learning control(PILCO)does not require an explicit global model as the actions are obtained by directly searching the policy space,the overfitting and lack of model complexity may still result in a large deviation between the prediction and the real system.Besides,none of these approaches consider the data error and measurement noise during the training process and test process,respectively.We propose a hierarchical Gaussian processes(GP)models,containing two layers of independent GPs,where the physically continuous probability transition model of the robot is obtained.Due to the physically continuous estimation,the algorithm overcomes the overfitting problem with a guaranteed model complexity,and the number of training data is also reduced.The policy for any given initial state is generated automatically by minimizing the expected cost according to the predefined cost function and the obtained probability distribution of the state.Furthermore,a novel Q(λ)based MFRL method scheme is employed to improve the policy.Simulation results show that the proposed RL algorithm is able to balance NAO robot on a rotating platform,and it is capable of adapting to the platform with varying angular velocity.
文摘Prof. Ren Fuji received his B.E. and M.E. degrees from Beijing University of Posts and Telecommunications, Beijing, China, in 1982 and 1985, respectively. He received his Ph.D. degree in 1991 from Hokkaido University, Japan. He is a professor in the Faculty of Engineering of the University of Tokushima, Japan. His research interests include natural language processing, artificial intelligence, language understanding and communication, and affective computing. He is a member of IEICE, CAAI, IEEJ, IPSJ, JSAI, AAMT, and IEEE. He is a fellow of the Japan Federation of Engineering Societies. He is the president of the International Advanced Information Institute and Vice Presidentof Chinese Association of Artificial Intelligence.
文摘A performance evaluation of sound recognition techniques in recognizing some spoken Arabic words, namely digits from zero to nine, is proposed. One of the main characteristics of aU Arabic digits is polysyllabic words except for zero. The performance analysis is based on different features of phonetic isolated Arabic digits. The main aim of this paper is to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on three recognition features： the Yule-Walker spectrum features, the Walsh spectrum features, and the Mel frequency Cepstral coefficients （MFCC） features. The MFCC based recognition system achieves the best average correct recognition. On the other hand, the Yule-Walker based recognition system achieves the worst average correct recognition.
基金partially supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI(JP23K24899)Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)(JPMJSP2145).
文摘The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.
基金supported by the“Chunhui”Program Collaborative Scientific Research Project(Grant No.202202004)Fundamental Research Program of Shanxi Province(Grant No.202303021222271)Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi,PR China(Grant No.2022L517).
文摘Prediction methods have garnered significant attention in intelligent decision-making.Most existing approaches to predicting crude oil prices prioritize accuracy and stability while providing precise prediction intervals that can offer valuable insights.Thus far,we introduced a novel hybrid model to forecast future crude oil prices.Our approach leverages the variational mode decomposition(VMD)to simplify the complexity of the original time series,yielding a set of subseries.These subseries are then modeled using a deep neural network architecture called a gated recurrent unit(GRU).To address the prediction uncertainty,we employed the pinball loss function rather than the mean square error to guide the proposed VMD-GRU.This adaptation extends the traditional GRUbased point forecasting to probabilistic forecasting by estimating quantiles.We evaluated our proposed model on a well-established crude oil price series by conducting both single-and multi-step-ahead forecasting analyses.Our findings underscore the efficacy of the combined model,demonstrating its superior predictive performance compared to benchmark models.
基金supported by National Natural Science Foundation of China(61872271,61673403,61873105,11972115)the Fundamental Research Funds for the Central Universities(22120190208)JSPS KAKENHI(JP17K12751)。
文摘A gravitational search algorithm(GSA)uses gravitational force among individuals to evolve population.Though GSA is an effective population-based algorithm,it exhibits low search performance and premature convergence.To ameliorate these issues,this work proposes a multi-layered GSA called MLGSA.Inspired by the two-layered structure of GSA,four layers consisting of population,iteration-best,personal-best and global-best layers are constructed.Hierarchical interactions among four layers are dynamically implemented in different search stages to greatly improve both exploration and exploitation abilities of population.Performance comparison between MLGSA and nine existing GSA variants on twenty-nine CEC2017 test functions with low,medium and high dimensions demonstrates that MLGSA is the most competitive one.It is also compared with four particle swarm optimization variants to verify its excellent performance.Moreover,the analysis of hierarchical interactions is discussed to illustrate the influence of a complete hierarchy on its performance.The relationship between its population diversity and fitness diversity is analyzed to clarify its search performance.Its computational complexity is given to show its efficiency.Finally,it is applied to twenty-two CEC2011 real-world optimization problems to show its practicality.
基金partially supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI(JP22H03643)Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)(JPMJSP2145)JST through the Establishment of University Fellowships towards the Creation of Science Technology Innovation(JPMJFS2115)。
文摘Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that reduces the power outputs of wind turbines located in downstream.Wind farm layout optimization(WFLO)aims to reduce the wake effect for maximizing the power outputs of the wind farm.Nevertheless,the wake effect among wind turbines increases significantly as the number of wind turbines increases in the wind farm,which severely affect power conversion efficiency.Conventional heuristic algorithms suffer from issues of low solution quality and local optimum for large-scale WFLO under complex wind scenarios.Thus,a chaotic local search-based genetic learning particle swarm optimizer(CGPSO)is proposed to optimize large-scale WFLO problems.CGPSO is tested on four larger-scale wind farms under four complex wind scenarios and compares with eight state-of-the-art algorithms.The experiment results indicate that CGPSO significantly outperforms its competitors in terms of performance,stability,and robustness.To be specific,a success and failure memories-based selection is proposed to choose a chaotic map for chaotic search local.It improves the solution quality.The parameter and search pattern of chaotic local search are also analyzed for WFLO problems.
基金This work was supported by the JSPS KAKENHI(JP17K12751 and JP15K00332).
文摘In this paper,a global optimum-based search strategy is proposed to alleviate the situation that the differential evolution(DE)usually sticks into a stagnation,especially on complex problems.It aims to reconstruct the balance between exploration and exploitation,and improve the search efficiency and solution quality of DE.The proposed method is activated by recording the number of recently consecutive unsuccessful global optimum updates.It takes the feedback from the global optimum,which makes the search strategy not only refine the current solution quality,but also have a change to find other promising space with better individuals.This search strategy is incorporated with various DE mutation strategies and DE variations.The experimental results indicate that the proposed method has remarkable performance in enhancing search efficiency and improving solution quality.
基金supported in part by the Doctoral Students’Short Term Study Abroad Scholarship Fund of Xidian Universitythe National Natural Science Foundation of China(61873342,61672400,62076189)+1 种基金the Recruitment Program of Global Expertsthe Science and Technology Development Fund,MSAR(0012/2019/A1)。
文摘In this paper,we elaborate on residual-driven Fuzzy C-Means(FCM)for image segmentation,which is the first approach that realizes accurate residual(noise/outliers)estimation and enables noise-free image to participate in clustering.We propose a residual-driven FCM framework by integrating into FCM a residual-related regularization term derived from the distribution characteristic of different types of noise.Built on this framework,a weighted?2-norm regularization term is presented by weighting mixed noise distribution,thus resulting in a universal residual-driven FCM algorithm in presence of mixed or unknown noise.Besides,with the constraint of spatial information,the residual estimation becomes more reliable than that only considering an observed image itself.Supporting experiments on synthetic,medical,and real-world images are conducted.The results demonstrate the superior effectiveness and efficiency of the proposed algorithm over its peers.
基金supported by the National Key R&D Program of China(2018AAA0101203)the National Natural Science Foundation of China(61673403,71601191)the JSPS KAKENHI(JP17K12751)。
文摘The multitrip pickup and delivery problem with time windows and manpower planning(MTPDPTW-MP)determines a set of ambulance routes and finds staff assignment for a hospital. It involves different stakeholders with diverse interests and objectives. This study firstly introduces a multiobjective MTPDPTW-MP(MO-MTPDPTWMP) with three objectives to better describe the real-world scenario. A multiobjective iterated local search algorithm with adaptive neighborhood selection(MOILS-ANS) is proposed to solve the problem. MOILS-ANS can generate a diverse set of alternative solutions for decision makers to meet their requirements. To better explore the search space, problem-specific neighborhood structures and an adaptive neighborhood selection strategy are carefully designed in MOILS-ANS. Experimental results show that the proposed MOILS-ANS significantly outperforms the other two multiobjective algorithms. Besides, the nature of objective functions and the properties of the problem are analyzed. Finally, the proposed MOILS-ANS is compared with the previous single-objective algorithm and the benefits of multiobjective optimization are discussed.
基金partially supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI(JP22H03643)Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)(JPMJSP2145)JST through the Establishment of University Fellowships Towards the Creation of Science Technology Innovation(JPMJFS2115)。
文摘Dear Editor,This letter presents a novel segmentation approach that leverages dendritic neurons to tackle the challenges of medical imaging segmentation.In this study,we enhance the segmentation accuracy based on a SegNet variant including an encoder-decoder structure,an upsampling index,and a deep supervision method.Furthermore,we introduce a dendritic neuron-based convolutional block to enable nonlinear feature mapping,thereby further improving the effectiveness of our approach.
基金supported in part by the Japan Society for the Promotion of Science (JSPS) KAKENHI (JP22H 03643)the Japan Science and Technology Agency (JST) (the establishment of university fellowships towards the creation of science technology innovation) (JPMJFS2115)。
文摘Dear Editor, This letter is concerned with the evolution strategy for addressing multi-objective feature selection problems in classification. Previous methods suffer from limitations such as being trapped in local optima and lacking stability. To overcome them, we propose a novel eliteguided mechanism based on information theory. Firstly, an elite solution is generated through a dimension reduction strategy and incorporated to the initialization population.
基金supported by Universiti Teknologi Malaysia under Research University Grant Scheme under Grant No.05J60 and No.04H35Ministry of Higher Education under Fundamental Research Grant Scheme under Grant No.4F317 and No.4F565Nigerian Education Trust Fund under Tertiary Education Trust Fund
文摘Ozone is a green house gas. Ozone absorption cross sections have been reported with discrepancies and inconsistencies. In this paper, simultaneous effects of the optical path length and temperature variations on ozone gas absorption cross sections are investigated at different wavelengths. HITRAN 2012, the latest available line list on spectralcalc.com simulator, is used in this study to simulate ozone gas absorption cross sections in relation to the simultaneous effects of the optical path length and temperature at the wavelengths of 603 nm and 575 nm. Results obtained for gas cells with the optical path length from 10 cm to 120 cm show that the decrease in temperatures from 313 K to 103 K results in the increase in ozone gas absorption cross sections. At wavelengths of 603 nm and 575 nm, the percentage increase of ozone gas absorption cross sections is 1.22% and 0.71%, respectively. Results obtained in this study show that in the visible spectrum, at constant pressure, ozone gas absorption cross sections are dependent on the temperature and wavelength but do not depend on the optical path length. Analysis in this work addresses discrepancies in ozone gas absorption cross sections in relation to the temperature in the visible spectrum; thus, the results can be applied to get optimal configuration of high accuracy ozone gas sensors.
文摘A permanent magnet linear synchronous motor （PMLSM） for a high temperature superconducting （HTS） maglev system has been studied, including the motor structure, control strategy, and analysis techniques. Finite element analysis （FEA） of magnetic field is conducted to accurately calculate major motor parameters. Equivalent electrical circuit is used to predict the drive＇s steady-state characteristics, and a phase variable model is applied to predict the dynamic performance. Preliminary experiment with a prototype has been made to verify the theoretical analysis and the HTS-PM synchronous driving technology.
文摘Demolition cementitious waste poses significant environmental challenges at the end of its lifecycle.To address this,fly ash(FA),a highly leachable material and a supplementary cementitious material,was combined with biochar(BC)to produce eco-friendly mortar bricks with reduced carbon emissions and contaminant leaching.BC was incorporated at 2%,4%,and 6%by weight,and the resulting blocks achieved compressive strengths of 8-12 MPa after 28 days,meeting Eurocode 6 standards for use in harsh conditions.Leaching tests under synthetic precipitation showed reductions in Al,Se,Ba,and Cr concentrations by 72%,48%,58%,and 53%,respectively,with 6%BC.While Al remained above drinking water limits,Cr levels dropped below limits when BC exceeded 4%.Leaching followed typical pH-dependent behaviour:Al exhibited an amphoteric trend,and Cr showed an oxyanionic trend,with minimal leaching at neutral pH.This study highlights the role of BC in reducing leaching potential in cementitious composites and provides critical data for geochemical modelling in sustainable demolition waste management systems.
基金financial support from the Australian Research Council Laureate Fellowships FL180100196。
文摘This study investigated the performances of a new type of precast beam-column joint subjected to earthquake and impact loads.For sustainability and durability considerations,new materials such as corrosion-resistant fibre reinforced polymer(FRP)bolts and reinforcements,fibre reinforced concrete(FRC),and geopolymer concrete(GPC)were used to construct the joint.To examine the resilience,durability,sustainability,and multi-hazard resistance capacities,both cyclic and pendulum impact tests were carried out.The experimental results demonstrated that the proposed precast joints had the comparable or even better performances as compared with the traditional monolithic joints under cyclic and impact loads.Numerical simulations using ABAQUS were also adopted to determine the optimal values of the concrete-end-plate(CEP)thickness for the proposed dry joints and to further quantify other response parameters which could not be obtained during the test,e.g.,stress distribution,energy absorption,and stress contours.Discussion on the influences of various parameters on joint performances under different loading conditions was also presented in this study.
