A Novel Approach to Heart Failure Prediction and Classification through Advanced Deep Learning Model

In this study, the author will investigate and utilize advanced machine learning models related to two different methodologies to determine the best and most effective way to predict individuals with heart failure and cardiovascular diseases. The first methodology involves a list of classification machine learning algorithms, and the second methodology involves the use of a deep learning algorithm known as MLP or Multilayer Perceptrons. Globally, hospitals are dealing with cases related to cardiovascular diseases and heart failure as they are major causes of death, not only for overweight individuals but also for those who do not adopt a healthy diet and lifestyle. Often, heart failures and cardiovascular diseases can be caused by many factors, including cardiomyopathy, high blood pressure, coronary heart disease, and heart inflammation [1]. Other factors, such as irregular shocks or stress, can also contribute to heart failure or a heart attack. While these events cannot be predicted, continuous data from patients’ health can help doctors predict heart failure. Therefore, this data-driven research utilizes advanced machine learning and deep learning techniques to better analyze and manipulate the data, providing doctors with informative decision-making tools regarding a person’s likelihood of experiencing heart failure. In this paper, the author employed advanced data preprocessing and cleaning techniques. Additionally, the dataset underwent testing using two different methodologies to determine the most effective machine-learning technique for producing optimal predictions. The first methodology involved employing a list of supervised classification machine learning algorithms, including Naïve Bayes (NB), KNN, logistic regression, and the SVM algorithm. The second methodology utilized a deep learning (DL) algorithm known as Multilayer Perceptrons (MLPs). This algorithm provided the author with the flexibility to experiment with different layer sizes and activation functions, such as ReLU, logistic (sigmoid), and Tanh. Both methodologies produced optimal models with high-level accuracy rates. The first methodology involves a list of supervised machine learning algorithms, including KNN, SVM, Adaboost, Logistic Regression, Naive Bayes, and Decision Tree algorithms. They achieved accuracy rates of 86%, 89%, 89%, 81%, 79%, and 99%, respectively. The author clearly explained that Decision Tree algorithm is not suitable for the dataset at hand due to overfitting issues. Therefore, it was discarded as an optimal model to be used. However, the latter methodology (Neural Network) demonstrated the most stable and optimal accuracy, achieving over 87% accuracy while adapting well to real-life situations and requiring low computing power overall. A performance assessment and evaluation were carried out based on a confusion matrix report to demonstrate feasibility and performance. The author concluded that the performance of the model in real-life situations can advance not only the medical field of science but also mathematical concepts. Additionally, the advanced preprocessing approach behind the model can provide value to the Data Science community. The model can be further developed by employing various optimization techniques to handle even larger datasets related to heart failures. Furthermore, different neural network algorithms can be tested to explore alternative approaches and yield different results.

Function of Cooperative Learning in Developing Positive Affect

This paper focus on the function of cooperative learning in developing positive affect,Including reducing anxiety,increasing motivation,facilitating the development of positive attitudes toward learning and language learning,promoting self-esteem,as well as supporting different learning styles and encouraging perseverance in the difficult and confusing process of learning a foreign language.

Effect of tetramethylpyrazine on the spatial learning and memory function of rats after focal cerebral ischemia

BACKGROUND： Tetramethylpyrazine （TMP） presents the effect of anti-platelet aggregation, reduces arteria resistance, increases cerebral blood flow, and improves microcirculation. OBJECTIVE： To observe the effects of TMP on the learning and memory abilities and the number of neurons in cortex and hippocampus after focal cerebral ischemia in rats DESIGN： A randomized controlled tria SETTING： Department of Human Anatomy and Histological Embryology, School of Medicine, Xi＇an Jiaotong University. MATERIALS： Fifty adult male Sprague-Dawley rats, weighing 250-300 g were supplied by the Experimental Animal Center, School of Medicine, Xi＇an Jiaotong University. TMP was purchased from Wuxi Seventh Pharmaceutical Co.Ltd （Lot Number： 2004051106, Specification： 2 mL/piece）. METHODS ： The experiments were carried out in School of Medicine of Xi＇an Jiaotong University from June 2004 to May 2005. The 50 rats were randomly divided into five groups according to the random number table method： sham-operated group, cerebral ischemia control group, low-dose TMP group, middle-dose TMP group and high-dose TMP group, 10 rats in each group. Rats in the TMP groups were immediately treated with intraperitoneal injection of TMP of 40, 80 and 120 mg/kg respectively, and those in the sham-operated group and cerebral ischemia control group were injected intraperitoneally by isovolume saline, once a day for 14 days successively. On the 15^th day, the spatial learning and memory abilities of the rats were assessed with the Morris water maze test, and then the changes of neuron numbers in cortex and hippocampus were observed by Nissl staining of brain sections. MAIN OUTCOME MEASURES ： The results of Morris water maze test and the changes of neuron numbers in cortex and hippocampus by Nissl staining of brain sections were observed. RESULTS： Finally 39 rats were involved in the analysis of results, and the other 11 died of excessive anesthesia or failure in model establishment. ① The rats in the cerebral ischemia control group manifested obvious spatial cognitive deficits in the place navigation trial and spatial probe trial. The mean values of escape latency in the sham-operated group, low, middle and high-dose TMP groups were obviously shorter than that in the cerebral ischemia control group [（23.92±2.21）, （41.84±3.74）, （39.50 ±3.80）, （31.38_±3.72）, （61.60±3.61） s, P 〈 0.05-0.01]. In the spatial probe trial, significant differences in the percentage of time spending in the former platform quadrant and frequency of crossing the former platform site in the sham-operated group, lose, middle and high-dose TMP groups were obviously higher or more than those in the cerebral ischemia control group [（36.27±3.42） %, （35.84±2.54）%, （38.43±3.08）%, （36.51±1.96）%, （22.24±3.46）%; （11 ±1 ）, （10±1）, （8_±1）, （8±1）, （4±1） times, P 〈 0.01]. ② In the morphological observation, the numbers of neurons in ipsilateral （left） parietal cortex in the sham-operated group, low, middle and high-dose TMP groups were obviously more than that in the cerebral ischemia control group [（98±8）, （65±5）, （53±6）, （57±6）, （37±6）/0.625 mm^2, P 〈 0.01], but the number of neurons in left hippocampus had no obvious differences among the groups （P 〉 0.05）. CONCLUSION ： TMP can improve obviously the spatial learning and memory function after permanent focal cerebral ischemia in rats, and the neuroprotective role of the drug in cortex may be involved in its mechanism.

DL-3-n-butylphthalide improved physical and learning and memory performance of rodents exposed to acute and chronic hypobaric hypoxia

Background:Studies have revealed the protective effect of DL-3-n-butylphthalide(NBP)against diseases associated with ischemic hypoxia.However,the role of NBP in animals with hypobaric hypoxia has not been elucidated.This study investigated the effects of NBP on rodents with acute and chronic hypobaric hypoxia.Methods:Sprague-Dwaley rats and Kunming mice administered with NBP(0,60,120,and 240 mg/kg for rats and 0,90,180,and 360 mg/kg for mice)were placed in a hypobaric hypoxia chamber at 10,000 m and the survival percentages at 30 min were determined.Then,the time and distance to exhaustion of drug-treated rodents were evaluated during treadmill running and motor-driven wheel-track treadmill experiments,conducted at 5800 m for 3 days or 20 days,to evaluate changes in physical functions.The frequency of active escapes and duration of active escapes were also determined for rats in a shuttle-box experiment,conducted at 5800 m for 6 days or 27 days,to evaluate changes in learning and memory function.ATP levels were measured in the gastrocnemius muscle and malonaldehyde(MDA),superoxide dismutase(SOD),hydrogen peroxide(H_(2)O_(2)),glutathione peroxidase(GSH-Px),and lactate were detected in sera of rats,and routine blood tests were also performed.Results:Survival analysis at 10,000 m indicated NBP could improve hypoxia tolerance ability.The time and distance to exhaustion for mice(NBP,90 mg/kg)and time to exhaustion for rats(NBP,120 and 240 mg/kg)significantly increased under conditions of acute hypoxia compared with control group.NBP treatment also significantly increased the time to exhaustion for rats when exposed to chronic hypoxia.Moreover,240 mg/kg NBP significantly increased the frequency of active escapes under conditions of acute hypoxia.Furthermore,the levels of MDA and H_(2)O_(2) decreased but those of SOD and GSH-Px in the sera of rats increased under conditions of acute and chronic hypoxia.Additionally,ATP levels in the gastrocnemius muscle significantly increased,while lactate levels in sera significantly decreased.Conclusion:NBP improved physical and learning and memory functions in rodents exposed to acute or chronic hypobaric hypoxia by increasing their anti-oxidative capacity and energy supply.

Machine Learning Kinetic Energy Functional for a One-Dimensional Periodic System

Kinetic energy(KE) functional is crucial to speed up density functional theory calculation. However, deriving it accurately through traditional physics reasoning is challenging. We develop a generally applicable KE functional estimator for a one-dimensional (1D) extended system using a machine learning method. Our end-to-end solution combines the dimensionality reduction method with the Gaussian process regression, and simple scaling method to adapt to various 1D lattices. In addition to reaching chemical accuracy in KE calculation, our estimator also performs well on KE functional derivative prediction. Integrating this machine learning KE functional into the current orbital free density functional theory scheme is able to provide us with expected ground state electron density.

Using junction trees for structural learning of Bayesian networks

The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas from local learning, constraint- based, and search-and-score techniques in a principled and ef- fective way. It first reconstructs the junction tree of a BN and then performs a K2-scoring greedy search to orientate the local edges in the cliques of junction tree. Theoretical and experimental results show the proposed algorithm is capable of handling networks with a large number of variables. Its comparison with the well-known K2 algorithm is also presented.

Improvement of learning and memory abilities and motor function in rats with cerebral infarction by intracerebral transplantation of neuron-like cells derived from bone marrow stromal cells

BACKGROUND： Transplantation of fetal cell suspension or blocks of fetal tissue can ameliorate the nerve function after the injury or disease in the central nervous system, and it has been used to treat neurodegenerative disorders induced by Parkinson disease. OBJECTIVE： To observe the effects of the transplantation of neuron-like cells derived from bone marrow stromal cells （rMSCs） into the brain in restoring the dysfunctions of muscle strength and balance as well as learning and memory in rat models of cerebral infarction. DESIGN ： A randomized controlled experiment.SETTING ： Department of Pathophysiology, Zhongshan Medical College of Sun Yat-sen University.MATERIALS ： Twenty-four male SD rats （3-4 weeks of age, weighing 200-220 g） were used in this study （Certification number：2001A027）. METHODS： The experiments were carried out in Zhongshan Medical College of Sun Yat-sen University between December 2003 and December 2004. ① Twenty-four male SD rats randomized into three groups with 8 rats in each： experimental group, control group and sham-operated group. Rats in the experiment al group and control group were induced into models of middle cerebral artery occlusion （MCAO）. After in vitro cultured, purified and identified with digestion, the Fischer344 rMSCs were induced to differentiate by tanshinone IIA, which was locally injected into the striate cortex （18 area） of rats in the experimental group, and the rats in the control group were injected by L-DMEM basic culture media （without serum） of the same volume to the corresponding brain area. In the sham-operated group, only muscle and vessel of neck were separated. ② At 2 and 8 weeks after the transplantation, the rats were given the screen test, prehensile-traction test, balance beam test and Morris water-maze test. ③ The survival and distribution of the induced cells in corresponding brain area were observed with Nissl stained with toluidine blue and hematoxylin and eosin （HE） staining in the groups.MAIN OUTCOME MEASURES ： ① Results of the behavioral tests （time of the Morris water-maze test screen test, prehensile-traction test, balance beam test）; ② Survival and distribution of the induced cells.RESULTS： All the 24 rats were involved in the analysis of results. ① Two weeks after transplantation, rats with neuron-like cells grafts in the experimental group had significant improvement on their general muscle strength than those in the control group [screen test： （9.4±1.7）, （4.7±1.0） s, P 〈 0.01]; forelimb muscle strength [prehensile-traction test： （7.6±1.4）, （5.2±1.2） s, P 〈 0.01], ability to keep balance [balance beam test： （7.9±0.74）, （6.1±0.91） s, P 〈 0.01] and abilities of learning and memory [latency to find the platform： （35.8±5.9）, （117.5±11.6） s, P 〈 0.01; distance： （623.1±43.4）, （1 902.3±98.6） cm, P 〈 0.01] as compared with those in the control group. The functional performances in the experimental group at 8 weeks were better than those at two weeks, which were still obviously different from those in the sham-operated group （P 〈 0.05）. ② The HE and Nissl stained brain tissue section showed that there was nerve cell proliferation at the infarcted cortex in the experiment group, the density was higher than that in the control group, plenty of aggregative or scattered cells could be observed at the site where needle was inserted for transplantation, the cells migrated directively towards the area around them, the cerebral vascular walls were wrapped by plenty of cells; In the control group, most of the cortices were destroyed, karyopyknosis and necrosis of neurons were observed, normal nervous tissue structure disappeared induced by edema, only some nerve fibers and glial cells remained.CONCLUSION： The rMSCs transplantation can obviously enhance the motor function and the abilities of learning and memory in rat models of cerebral infarction.

Correlation between special brain area and blood perfusion in patients with cerebral infarction at convalescent period Feasibility for quantitative determination and estimation of learning and memory function

BACKGROUND： Presently, clinic memory scale is used to evaluate learning memory ability in most studies, and the influence of difference in measurement condition of individuals exists. OBJECTIVE： To study the correlation between regional cerebral blood flow （rCBF） perfusion and learning memory function in special brain regions of patients with cerebral infarction at convalescent period, and to try to find out a method which can quantitatively evaluate learning ability. DESIGN： Case observation, and correlation analysis. SETTINGS： Shandong Institute for Behavioral Medicine; the Affiliated Hospital of Jining Medical College. PARTICIPANTS： Totally 70 patients with cerebral infarction admitted to Department of Neurology, Jining Medical College between January 2004 and December 2005 were involved. The involved patients, 58 male and 12 female, were averaged （52±3） years, and they were all right handed. They all met the diagnosis criteria instituted by the Fourth National Conference on Cerebrovascular Disease, and were confirmed as cerebral infarction by skull CT or MRI. Informed consents of detected items were obtained from all the patients and relatives. METHODS： When the patients were at convalescent period, their learning and memory ability were measured with “ clinic memory scale （set A）”. The 18 patients whose total mark over 100 were regarded as good learning memory function group; The 23 cases whose total mark less than 70 were regarded as poor learning memory function group. RCBF of hippocampus, nucleus amygdalae, temporal cortex and prefrontal lobe of patients between two groups were measured and compared by single photon emission computed tomography （SPECT）. The total scores of the 18 good learning memory patients and 23 poor learning memory patients were taken as dependent variable Y, and their rCBFs of hippocampus, nucleus amygdale, temporal cortex and prefrontal lobe respectively as independent variable X for linear correlation analysis. MAIN OUTCOME MEASURES： Correlation of rCBF in different brain regions and learning memory ability in patients with cerebral infarction. RESULTS： ①The rCBF of hippocampus, nucleus amygdale, temportal cortex and prefrontal cortex of good learning memory function group were significantly higher than those of poor learning memory function group （P 〈 0.05）. ②In the good learning memory function group, rCBF of hippocampus, nucleus amygdale, temportal cortex and prefrontal cortex were significantly positively correlated with memory scale scores （ r = 0.961, 0.926, 0.954, 0.907, P 〈 0.05 ） , and also in the poor learning memory function group （r = 0.979, 0.976, 0.991, 0.953, P 〈 0.05 ） . CONCLUSION： The rCBF of hippocampus, nucleus amygdale, temportal cortex and prefrontal cortex of patients with cerebral infarction are significantly positively correlated with memory scale scores. Predicting learning memory ability of patients by quantitative determination of rCBF provides a quantitative and objective method for evaluating learning memory ability.

Tongdu Tiaoshen Acupuncture Method for Promoting Hippocampal Nerve Repair and Regeneration and Improving Learning and Memory Dysfunction in Stroke Model Rats

[Objectives]To evaluate the effects of Tongdu Tiaoshen Acupuncture method on improving learning and memory function and hippocampal nerve regeneration and repair after stroke.[Methods]Animal models of cognitive impairment in the recovery phase of cerebral infarction in rats were prepared,and rats were randomly divided into control group,model group,donepezil group,and acupuncture group.Morris water maze experiment was carried out to evaluate learning and memory ability.Nissl staining,BrdU and DCX immunofluorescence staining were used to observe the number and morphological structure of neuronal pyramidal and granular cells in the dentate gyrus(DG)area of the hippocampus,as well as the proliferation and differentiation of neural progenitor cells.TUNEL method was used to detect cell apoptosis.[Results]Before intervention,the scores and ELP of the model group,donepezil group and acupuncture group were significantly higher than those of the blank group(P<0.05);after the intervention,the neurological scores and ELP of the blank group and the model group were not significantly different from those before the intervention(P<0.05);the donepezil group and acupuncture group were significantly reduced,there was no difference between the donepezil group and acupuncture group(P>0.05),but it was still significantly higher than the blank group(P<0.05).The results of BrdU and DCX immunofluorescence staining showed that there were only a few BrdU positive cells and DCX protein in the hippocampal DG area of mice in the blank group,and the positive cells in the model group were significantly increased(P<0.05);donepezil group and acupuncture group showed significant increase compared with the model group(P<0.05);compared with the blank group,the number of neurons in the hippocampal DG area of each group was significantly reduced(P<0.01),and the neuronal apoptosis index was significantly increased(P<0.01);compared with the blank group,the number of neurons in the hippocampal DG area of each group was significantly reduced(P<0.01),and the neuronal apoptosis index was significantly increased(P<0.01).The number of neurons in the hippocampal DG area of rats in the acupuncture group and donepezil group was significantly increased(P<0.01),and the neuronal apoptosis index was significantly decreased(P<0.01).[Conclusions]Tongdu Tiaoshen Acupuncture method can improve the learning and memory function of stroke model rats by promoting the regeneration and repair of hippocampal nerve in rats with cerebral infarction.

Synergistic application of molecular docking and machine learning for improved binding pose

Accurate prediction of protein-ligand complex structures is a crucial step in structure-based drug design.Traditional molecular docking methods exhibit limitations in terms of accuracy and sampling space,while relying on machine-learning approaches may lead to invalid conformations.In this study,we propose a novel strategy that combines molecular docking and machine learning methods.Firstly,the protein-ligand binding poses are predicted using a deep learning model.Subsequently,position-restricted docking on predicted binding poses is performed using Uni-Dock,generating physically constrained and valid binding poses.Finally,the binding poses are re-scored and ranked using machine learning scoring functions.This strategy harnesses the predictive power of machine learning and the physical constraints advantage of molecular docking.Evaluation experiments on multiple datasets demonstrate that,compared to using molecular docking or machine learning methods alone,our proposed strategy can significantly improve the success rate and accuracy of protein-ligand complex structure predictions.

Effects of repetitive transcranial magnetic stimulation on cognitive function and cholinergic activity in the rat hippocampus after vascular dementia

Repetitive transcranial magnetic stimulation （rTMS） is a non-invasive treatment that can enhance the recovery of neurological function after stroke. Whether it can similarly promote the recovery of cognitive function after vascular dementia remains unknown, In this study, a rat model for vascular dementia was established by the two-vessel occlusion method. Two days after injury, 30 pulses of rTMS were ad- ministered to each cerebral hemisphere at a frequency of 0.5 Hz and a magnetic field intensity of 1,33 T. The Morris water maze test was used to evaluate learning and memory function. The Karnovsky-Roots method was performed to determine the density of cholinergic neurons in the hippocampal CA1 region. Immunohistochemical staining was used to determine the number of brain-derived neurotroph- ic factor （BDNF）-immunoreactive cells in the hippocampal CA1 region, rTMS treatment for 30 days significantly improved learning and memory function, increased acetylcholinesterase and choline acetyltransferase activity, increased the density of cholinergic neurons, and increased the number of BDNF-immunoreactive cells. These results indicate that rTMS can ameliorate learning and memory deficiencies in rats with vascular dementia, The mechanism through which this occurs might be related to the promotion of BDNF expression and subsequent restoration of cholinergic system activity in hippocampal CA 1 region.

The potential of endogenous neurogenesis for brain repair and regeneration following traumatic brain injury

Traumatic brain injury （TBI） is the leading cause of death and disability of persons under 45 years old in the United States, affecting over 1.5 million individtials each year. It had been th ought that recovery from such injuries is severely limited due to the inability of the adult bra in to replace damaged neurons. However, recent studies indicate that the mature mammalian central nervous system （CNS） has the potential to replenish damaged neurons by proliferation and neuronal differentiation of adult neural stem/progenitor cells residing in the neurogenic regions in the brain. Furthermore, increasing evidence indicates that these endogenous stem/ progenitor cells may play regenerative and reparative roles in response to CNS injuries or diseases. In support of this notion, heightened levels of cell proliferation and neurogenesis have been ob- served in response to brain trauma or insults suggesting that the brain has the inherent potential to restore populations of damaged or destroyed neurons. This review will discuss the potential functions of adult neurogenesis and recent development of strategies aiming at harnessing this neurogenic capacity in order to repopulate and repair the injured brain.

Effect of Cistanche Desertica Polysaccharides on Learning and Memory Functions and Ultrastructure of Cerebral Neurons in Experimental Aging Mice

To observe the effects of Cistanche desertica polysaccharides (CDP) on the learning and memory functions and cerebral ultrastructure in experimental aging mice. Methods: CDP was administrated intragastrically 50 or 100 mg/kg per day for 64 successive days to experimental aging model mice induced by D-galactose, then the learning and memory functions of mice were estimated by step-down test and Y-maze test; organelles of brain tissue and cerebral ultrastructure were observed by transmission electron microscope and physical strength was determined by swimming test. Results: CDP could obviously enhance the learning and memory functions (P＜0.01) and prolong the swimming time (P＜0.05), decrease the number of lipofuscin and slow down the degeneration of mitochondria in neurons(P＜0.05), and improve the degeneration of cerebral ultra-structure in aging mice. Conclusion: CDP could improve the impaired physiological function and alleviate cerebral morphological change in experimental aging mice.

Effects of special brain area regional cerebral blood flow abnormal perfusion on learning and memory function and its molecular mechanism in rats

To study the effect of special brain area regional cerebral blood flow(rCBF)abnormal perfusion on learning and memory function and its molecular mechanism,64 adult male healthy Sprague-Dawley(SD)rats were randomly divided into two groups,the false operation group(control group)and the operation group(model group).After surgical operation,the operation group undertook bilateral common carotid artery permanent ligation,while the other group did not.Learning and memory function were measured by Y-maze at 4 h,8 h,24 h and 3 d after surgical operation,respectively.The rCBF of the right frontal lobe and hippocampus was also detected by the PerifluxPF model laser Doppler flowmetry,and the expressions of c-fos or c-jun or Bcl-2 and Bax were also measured by immune histochemistry S-P method accordingly.Results showed that the rCBF of the right frontal lobe and hippocampus in the operation group was significantly lower than that in the false operation group(P,0.05).The learning indexes,error number(EN),day of reach standard and total reaction time(TRT)in the operation group,were significantly higher than that in the false operation group(P,0.05).However,the initiative evasion rate in the operation group was significantly lower than that in the false operation group.The study also found that the rCBF was relatively more,the indexes(EN,the day of reach standard and TRT)relatively fewer,but the initiative evasion rate and the memory keeping rate were relatively more.The positive expression and the average absorbency of Fos and Jun in the operation group were significantly higher than that in the false operation group(P<0.05).Furthermore,Bax and Bcl-2 positive cells were all increased over time in the operation group,and the expression ratio of Bax/Bcl-2 in the operation group was significantly higher than that in the false operation group(P<0.01).In conclusion,rCBF decrease can impair the learning and memory function in rats,which may be related to the increase of the expression ratio of c-fos or c-jun or Bcl-2 or Bax in the frontal cortex and hippocampus.

Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review

The paper reviews and extends an emerging body of theoretical results on deep learning including the conditions under which it can be exponentially better than shallow learning. A class of deep convolutional networks represent an important special case of these conditions, though weight sharing is not the main reason for their exponential advantage. Implications of a few key theorems are discussed, together with new results, open problems and conjectures.

Safety lifetime analysis method for multi-mode time-dependent structural system

It is important to determine the safety lifetime of Multi-mode Time-Dependent Structural System(MTDSS). However, there is still a lack of corresponding analysis methods.Therefore, this paper establishes MTDSS safety lifetime model firstly, and then proposes a Kriging surrogate model based method to estimate safety lifetime. The first step of proposed method is to construct the Kriging model of MTDSS performance function by using extremum learning function. By identifying possible extremum mode of MTDSS, the performance function of MTDSS can be equivalently transformed into the one of Single-mode Time-Dependent Structure(STDS).The second step is to use the Advanced First Failure Instant Learning Function(AFFILF) to train the Kriging model constructed in the first step, so that the convergent Kriging model can identify the possible First Failure Instant(FFI) of STDS. Then safety lifetime can be searched quickly by dichotomy search. By using AFFILF, the minimum instant that the state is not accurately identified by the current Kriging model is selected as the training point, which avoids the unnecessary calculation which may be introduced into the existing First Failure Instant Learning Function(FFILF).In addition, the Candidate Sample Pool(CSP) reduction strategy is also adopted. By adaptively deleting the random candidate sample points whose FFI have been accurately identified by the current Kriging model, the training efficiency is further improved. Three cases show that the proposed method is accurate and efficient.

Efficient adaptive Kriging for system reliability analysis with multiple failure modes under random and interval hybrid uncertainty

In the field of the system reliability analysis with multiple failure modes,the advances mainly involve only random uncertainty.The upper bound of the system failure probability with multiple failure modes is usually employed to quantify the safety level under Random and Interval Hybrid Uncertainty(RI-HU).At present,there is a lack of an efficient and accurate method for estimating the upper bound of the system failure probability.This paper proposed an efficient Kriging model based on numerical simulation algorithm to solve the system reliability analysis under RI-HU.This method proposes a system learning function to train the system Kriging models of the system limit state surface.The convergent Kriging models are used to replace the limit state functions of the system multi-mode for identifying the state of the random sample.The proposed system learning function can adaptively select the failure mode contributing most to the system failure probability from the system and update its Kriging model.Thus,the efficiency of the Kriging training process can be improved by avoiding updating the Kriging models contributing less to estimating the system failure probability.The presented examples illustrate the superiority of the proposed method.