Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up t...Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.展开更多
In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying result...In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes.展开更多
Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it...Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it avoids converging to the local optimum. However, it takes too much CPU time in the late process of GA. On the other hand, in the late process Simulated Annealing (SA) converges faster than GA but it is easily trapped to local optimum. In this letter, a useful method that unifies GA and SA is introduced, which utilizes the advantage of the global search ability of GA and fast convergence of SA. The experimental results show that the proposed algorithm outperforms GA in terms of CPU time without degradation of performance. It also achieves highly comparable placement cost compared to the state-of-the-art results obtained by Versatile Place and Route (VPR) Tool.展开更多
Experiment statistical method and genetic algorithms based optimization method are used to obtain the optimum differential gear ratio for heavy truck that provides best fuel consumption when changing the working condi...Experiment statistical method and genetic algorithms based optimization method are used to obtain the optimum differential gear ratio for heavy truck that provides best fuel consumption when changing the working condition that affects its torque and speed range. The aim of the study is to obtain the optimum differential gear ratio with fast and accurate optimization calculation without affecting drivability characteristics of the vehicle according to certain driving cycles that represent the new working conditions of the truck. The study is carried on a mining dump truck YT3621 with 9 for- ward shift manual transmission. Two loading conditions, no load and 40 t, and four on road real driving cycles have been discussed. The truck powertrain is modeled using GT-drive, and DOE -post processing tool of the GT-suite is used for DOE analysis and genetic algorithm optimization.展开更多
The molecular compositions and stable carbon and hydrogen isotopic compositions of natural gas from the Xinchang gas field in the Sichuan Basin were investigated to determine the genetic types. The natural gas is main...The molecular compositions and stable carbon and hydrogen isotopic compositions of natural gas from the Xinchang gas field in the Sichuan Basin were investigated to determine the genetic types. The natural gas is mainly composed of methane （88.99%-98.01%）, and the dryness coefficient varies between 0.908 and 0.997. The gas generally displays positive alkane carbon and hydrogen isotopic series. The geochemical characteristics and gas-source correlation indicate that the gases stored in the 5th member of the Upper Triassic Xujiahe Formation are coal-type gases which are derived from source rocks in the stratum itself. The gases reservoired in the 4th member of the Xujiahe Formation and Jurassic strata in the Xinchang gas field are also coal-type gases that are derived from source rocks in the 3rd and 4th members of the Xujiahe Formation. The gases reservoired in the 2nd member of the Upper Triassic Xujiahe Formation are mainly coal-type gases with small amounts of oil-type gas that is derived from source rocks in the stratum itself. This is accompanied by a small amount of contribution brought by source rocks in the Upper Triassic Ma＇antang and Xiaotangzi formations. The gases reservoired in the 4th member of the Middle Triassic Leikoupo Formation are oil-type gases and are believed to be derived from the secondary cracking of oil which is most likely to be generated from the Upper Permian source rocks.展开更多
Accurate prediction of chemical composition of vacuum gas oil （VGO） is essential for the routine operation of refineries. In this work, a new approach for auto-design of artificial neural networks （ANN） based on a...Accurate prediction of chemical composition of vacuum gas oil （VGO） is essential for the routine operation of refineries. In this work, a new approach for auto-design of artificial neural networks （ANN） based on a genetic algorithm （GA） is developed for predicting VGO saturates. The number of neurons in the hidden layer, the momentum and the learning rates are determined by using the genetic algorithm. The inputs for the artificial neural networks model are five physical properties, namely, average boiling point, density, molecular weight, viscosity and refractive index. It is verified that the genetic algorithm could find the optimal structural parameters and training parameters of ANN. In addition, an artificial neural networks model based on a genetic algorithm was tested and the results indicated that the VGO saturates can be efficiently predicted. Compared with conventional artificial neural networks models, this approach can improve the prediction accuracy.展开更多
Great volumes of shallow-buried （〈2,000 m） natural gases which are mainly composed of biogases and low-mature gases have been found in the Mesozoic-Cenozoic sedimentary basins in China. Many shallow gas reservoirs ...Great volumes of shallow-buried （〈2,000 m） natural gases which are mainly composed of biogases and low-mature gases have been found in the Mesozoic-Cenozoic sedimentary basins in China. Many shallow gas reservoirs in China are characterized by coexistence of biogas and low-mature gas, so identifying the genetic types of shallow gases is important for exploration and development in sedimentary basins. In this paper, we study the gas geochemistry characteristics and distribution in different basins, and classify the shallow gas into two genetic types, biogas and low-mature gas. The biogases are subdivided further into two subtypes by their sources, the source rock-derived biogas and hydrocarbon-derived biogas. Based on the burial history of the source rocks, the source rock-derived biogases are divided into primary and secondary biogas. The former is generated from the source rocks in the primary burial stage, and the latter is from uplifted source rocks or those in a secondary burial stage. In addition, the identifying parameters of each type of shallow gas are given. Based on the analysis above, the distributions of each type of shallow gas are studied. The primary biogases generated from source rocks are mostly distributed in Quaternary basins or modem deltas. Most of them migrate in watersoluble or diffused mode, and their migration distance is short. Reservoir and caprock assemblages play an important role in primary biogas accumulation. The secondary biogases are distributed in a basin with secondary burial history. The oil-degraded biogases are distributed near heavy oil pools. The low-mature gases are widely distributed in shallow-buried reservoirs in the Meso-Cenozoic basins.展开更多
Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presen...Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presents a new digital watermarking scheme that combines some operators of the Genetic Algorithm (GA) and the Residue Number (RN) System (RNS) to perform encryption on an image, which is embedded into a cover image for the purposes of watermarking. Thus, an image watermarking scheme uses an encrypted image. The secret image is embedded in decomposed frames of the cover image achieved by applying a three-level Discrete Wavelet Transform (DWT). This is to ensure that the secret information is not exposed even when there is a successful attack on the cover information. Content creators can prove ownership of the multimedia content by unveiling the secret information in a court of law. The proposed scheme was tested with sample data using MATLAB2022 and the results of the simulation show a great deal of imperceptibility and robustness as compared to similar existing schemes.展开更多
As a kind of abnormal natural gas formed with special mechanism, the deep-basin gas, accumulated in the lower parts of a basin or syncline and trapped by a tight reservoir, has such characteristics as gas-water invers...As a kind of abnormal natural gas formed with special mechanism, the deep-basin gas, accumulated in the lower parts of a basin or syncline and trapped by a tight reservoir, has such characteristics as gas-water inversion, abnormal pressure, continuous distribution and tremendous reserves. Being a geological product of the evolution of petroliferous basins by the end of the middle-late stages, the formation of a deep-basin gas accumulation must meet four conditions, i.e., continuous and sufficient gas supply, tight reservoirs in continuous distribution, good sealing caps and stable structures. The areas, where the expansion force of natural gas is smaller than the sum of the capillary force and the hydrostatic pressure within tight reservoirs, are favorable for forming deep-basin gas pools. The range delineated by the above two forces corresponds to that of the deep-basin gas trap. Within the scope of the deep-basin gas trap, the balance relationship between the amounts of ingoing and overflowing gases determines the gas-bearing area of the deep-basin gas pool. The gas volume in regions with high porosity and high permeability is worth exploring under current technical conditions and it is equivalent to the practical resources (about 10%-20% of the deep-basin gas). Based on studies of deep-basin gas formation conditions, the theory of force balance and the equation of material balance, the favorable areas and gas-containing ranges, as well as possible gas-rich regions are preliminarily predicted in the deep-basin gas pools in the Upper Paleozoic He-8 segment of the Ordos basin.展开更多
基金Research Supporting Project Number(RSPD2023R 585),King Saud University,Riyadh,Saudi Arabia.
文摘Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.
基金Project supported by the National Basic Research Program (973) of China (No. 2002CB312200) and the Center for Bioinformatics Pro-gram Grant of Harvard Center of Neurodegeneration and Repair,Harvard Medical School, Harvard University, Boston, USA
文摘In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes.
基金Supported by School of Engineering, Napier University, United Kingdom, and partially supported by the National Natural Science Foundation of China (No.60273093).
文摘Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it avoids converging to the local optimum. However, it takes too much CPU time in the late process of GA. On the other hand, in the late process Simulated Annealing (SA) converges faster than GA but it is easily trapped to local optimum. In this letter, a useful method that unifies GA and SA is introduced, which utilizes the advantage of the global search ability of GA and fast convergence of SA. The experimental results show that the proposed algorithm outperforms GA in terms of CPU time without degradation of performance. It also achieves highly comparable placement cost compared to the state-of-the-art results obtained by Versatile Place and Route (VPR) Tool.
文摘Experiment statistical method and genetic algorithms based optimization method are used to obtain the optimum differential gear ratio for heavy truck that provides best fuel consumption when changing the working condition that affects its torque and speed range. The aim of the study is to obtain the optimum differential gear ratio with fast and accurate optimization calculation without affecting drivability characteristics of the vehicle according to certain driving cycles that represent the new working conditions of the truck. The study is carried on a mining dump truck YT3621 with 9 for- ward shift manual transmission. Two loading conditions, no load and 40 t, and four on road real driving cycles have been discussed. The truck powertrain is modeled using GT-drive, and DOE -post processing tool of the GT-suite is used for DOE analysis and genetic algorithm optimization.
基金financially supported by the National Natural Science Foundation of China (grants No.41625009, 41302118 and U1663201)the National Key Foundational Research and Development Project (Grant No:2016YFB0600804)the National Science & Technology Special Project (grant No.2016ZX05002-006)
文摘The molecular compositions and stable carbon and hydrogen isotopic compositions of natural gas from the Xinchang gas field in the Sichuan Basin were investigated to determine the genetic types. The natural gas is mainly composed of methane （88.99%-98.01%）, and the dryness coefficient varies between 0.908 and 0.997. The gas generally displays positive alkane carbon and hydrogen isotopic series. The geochemical characteristics and gas-source correlation indicate that the gases stored in the 5th member of the Upper Triassic Xujiahe Formation are coal-type gases which are derived from source rocks in the stratum itself. The gases reservoired in the 4th member of the Xujiahe Formation and Jurassic strata in the Xinchang gas field are also coal-type gases that are derived from source rocks in the 3rd and 4th members of the Xujiahe Formation. The gases reservoired in the 2nd member of the Upper Triassic Xujiahe Formation are mainly coal-type gases with small amounts of oil-type gas that is derived from source rocks in the stratum itself. This is accompanied by a small amount of contribution brought by source rocks in the Upper Triassic Ma＇antang and Xiaotangzi formations. The gases reservoired in the 4th member of the Middle Triassic Leikoupo Formation are oil-type gases and are believed to be derived from the secondary cracking of oil which is most likely to be generated from the Upper Permian source rocks.
文摘Accurate prediction of chemical composition of vacuum gas oil （VGO） is essential for the routine operation of refineries. In this work, a new approach for auto-design of artificial neural networks （ANN） based on a genetic algorithm （GA） is developed for predicting VGO saturates. The number of neurons in the hidden layer, the momentum and the learning rates are determined by using the genetic algorithm. The inputs for the artificial neural networks model are five physical properties, namely, average boiling point, density, molecular weight, viscosity and refractive index. It is verified that the genetic algorithm could find the optimal structural parameters and training parameters of ANN. In addition, an artificial neural networks model based on a genetic algorithm was tested and the results indicated that the VGO saturates can be efficiently predicted. Compared with conventional artificial neural networks models, this approach can improve the prediction accuracy.
文摘Great volumes of shallow-buried （〈2,000 m） natural gases which are mainly composed of biogases and low-mature gases have been found in the Mesozoic-Cenozoic sedimentary basins in China. Many shallow gas reservoirs in China are characterized by coexistence of biogas and low-mature gas, so identifying the genetic types of shallow gases is important for exploration and development in sedimentary basins. In this paper, we study the gas geochemistry characteristics and distribution in different basins, and classify the shallow gas into two genetic types, biogas and low-mature gas. The biogases are subdivided further into two subtypes by their sources, the source rock-derived biogas and hydrocarbon-derived biogas. Based on the burial history of the source rocks, the source rock-derived biogases are divided into primary and secondary biogas. The former is generated from the source rocks in the primary burial stage, and the latter is from uplifted source rocks or those in a secondary burial stage. In addition, the identifying parameters of each type of shallow gas are given. Based on the analysis above, the distributions of each type of shallow gas are studied. The primary biogases generated from source rocks are mostly distributed in Quaternary basins or modem deltas. Most of them migrate in watersoluble or diffused mode, and their migration distance is short. Reservoir and caprock assemblages play an important role in primary biogas accumulation. The secondary biogases are distributed in a basin with secondary burial history. The oil-degraded biogases are distributed near heavy oil pools. The low-mature gases are widely distributed in shallow-buried reservoirs in the Meso-Cenozoic basins.
文摘Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presents a new digital watermarking scheme that combines some operators of the Genetic Algorithm (GA) and the Residue Number (RN) System (RNS) to perform encryption on an image, which is embedded into a cover image for the purposes of watermarking. Thus, an image watermarking scheme uses an encrypted image. The secret image is embedded in decomposed frames of the cover image achieved by applying a three-level Discrete Wavelet Transform (DWT). This is to ensure that the secret information is not exposed even when there is a successful attack on the cover information. Content creators can prove ownership of the multimedia content by unveiling the secret information in a court of law. The proposed scheme was tested with sample data using MATLAB2022 and the results of the simulation show a great deal of imperceptibility and robustness as compared to similar existing schemes.
基金This study is part of the National Key Basic Research Project(973)of the"Formation and Distribution of Oil and Gas in Typical Superimposed Basins in China(G19990433)"supported by the Ministry of Science and Technology of China.
文摘As a kind of abnormal natural gas formed with special mechanism, the deep-basin gas, accumulated in the lower parts of a basin or syncline and trapped by a tight reservoir, has such characteristics as gas-water inversion, abnormal pressure, continuous distribution and tremendous reserves. Being a geological product of the evolution of petroliferous basins by the end of the middle-late stages, the formation of a deep-basin gas accumulation must meet four conditions, i.e., continuous and sufficient gas supply, tight reservoirs in continuous distribution, good sealing caps and stable structures. The areas, where the expansion force of natural gas is smaller than the sum of the capillary force and the hydrostatic pressure within tight reservoirs, are favorable for forming deep-basin gas pools. The range delineated by the above two forces corresponds to that of the deep-basin gas trap. Within the scope of the deep-basin gas trap, the balance relationship between the amounts of ingoing and overflowing gases determines the gas-bearing area of the deep-basin gas pool. The gas volume in regions with high porosity and high permeability is worth exploring under current technical conditions and it is equivalent to the practical resources (about 10%-20% of the deep-basin gas). Based on studies of deep-basin gas formation conditions, the theory of force balance and the equation of material balance, the favorable areas and gas-containing ranges, as well as possible gas-rich regions are preliminarily predicted in the deep-basin gas pools in the Upper Paleozoic He-8 segment of the Ordos basin.
