Integrated Analysis Method Research Articles

Predicting China’s carbon intensity through 2050: an integrated analysis method

ABSTRACT Carbon intensity is one of the key indexes in the process of decarbonizing development. Therefore, our paper investigates possible pathways of China’s carbon intensity to 2050 depending on China’s development stage and trends. We first investigate the major influence factors of carbon intensity based on the Kaya identity, and then forecast China’s future carbon intensity with a generalized regression neural network model coupled with a scenario analysis with official data from 1978 to 2020. Our results show that: (1) China’s carbon intensity will decrease under the benchmark growth, high growth, and low growth scenarios but vary by amounts and rates of decrease due to the settings of the influences factors; (2) China is able to achieve the reduction targets of 2025 under the benchmark growth and low growth scenario, but cannot achieve the target under the high grow scenario. However, China can meet its reduction target by 2030 in all scenarios. (3) The Chinese government should aim to reduce carbon intensity by 23–25%, 40–44% and 64–70% by 2035, 2040 and 2050 as compared to the level in 2030. Therefore, China should keep promoting the deep low-carbon transformation of economic development model, and realize high-quality economic development in order to achieve these objectives.

Statistical analysis of spatially resolved transcriptomic data by incorporating multiomics auxiliary information.

Effective control of false discovery rate is key for multiplicity problems. Here, we consider incorporating informative covariates from external datasets in the multiple testing procedure to boost statistical power while maintaining false discovery rate control. In particular, we focus on the statistical analysis of innovative high-dimensional spatial transcriptomic data while incorporating external multiomics data that provide distinct but complementary information to the detection of spatial expression patterns. We extend OrderShapeEM, an efficient covariate-assisted multiple testing procedure that incorporates one auxiliary study, to make it permissible to incorporate multiple external omics studies, to boost statistical power of spatial expression pattern detection. Specifically, we first use a recently proposed computationally efficient statistical analysis method, spatial pattern recognition via kernels, to produce the primary test statistics for spatial transcriptomic data. Afterwards, we construct the auxiliary covariate by combining information from multiple external omics studies, such as bulk and single-cell RNA-seq data using the Cauchy combination rule. Finally, we extend and implement the integrative analysis method OrderShapeEM on the primary P-values along with auxiliary data incorporating multiomics information for efficient covariate-assisted spatial expression analysis. We conduct a series of realistic simulations to evaluate the performance of our method with known ground truth. Four case studies in mouse olfactory bulb, mouse cerebellum, human breast cancer, and human heart tissues further demonstrate the substantial power gain of our method in detecting genes with spatial expression patterns compared to existing classic approaches that do not utilize any external information.

A Survey of Statistical Methods for Microbiome Data Analysis

In the last decade, numerous statistical methods have been developed for analyzing microbiome data generated from high-throughput next-generation sequencing technology. Microbiome data are typically characterized by zero inflation, overdispersion, high dimensionality, and sample heterogeneity. Three popular areas of interest in microbiome research requiring statistical methods that can account for the characterizations of microbiome data include detecting differentially abundant taxa across phenotype groups, identifying associations between the microbiome and covariates, and constructing microbiome networks to characterize ecological associations of microbes. These three areas are referred to as differential abundance analysis, integrative analysis, and network analysis, respectively. In this review, we highlight available statistical methods for differential abundance analysis, integrative analysis, and network analysis that have greatly advanced microbiome research. In addition, we discuss each method's motivation, modeling framework, and application.

Quantitative Data Integration Analysis Method for Cross-Studies: Obstructive Sleep Apnea as an Example.

Objective In recent years, the prevalence of obstructive sleep apnea (OSA) has gradually increased. The diagnosis of this multiphenotypic disorder requires a combination of several indicators. The objective of this study was to find significant apnea monitor indicators of OSA by developing a strategy for cross-study screening and integration of quantitative data. Methods Articles related to sleep disorders were obtained from the PubMed database. A sleep disorder dataset and an OSA dataset were manually curated from these articles. Two evaluation indexes, the indicator coverage ratio (ICR) and the study integrity ratio (SIR), were used to filter out OSA indicators from the OSA dataset and create profiles including different numbers of indicators and studies for analysis. Data were analyzed by the meta 4.18-0 package of R, and the p value and standard mean difference (SMD) values were calculated to evaluate the change of each indicator. Results The sleep disorder dataset was constructed based on 178 studies from 119 publications, the OSA dataset was extracted from 89 studies, 284 sleep-related indicators were filtered out, and 22 profiles were constructed. Apnea hypopnea index was significantly decreased in all 22 profiles. Total sleep time (TST) (min) showed no significant differences in 21 profiles. There were significant increases in rapid eye movement (REM) (%TST) in 18 profiles, minimum arterial oxygen saturation (SaO2) in 9 profiles, REM duration in 3 profiles, and slow wave sleep duration (%TST) and pulse oximetry lowest point in 2 profiles. There were significant decreases in apnea index (AI) in 14 profiles; arousal index and SaO2 < 90 (%TST) in 8 profiles; N1 stage (%TST) in 7 profiles; and hypopnea index, N1 stage (% sleep period time (%SPT)), N2 stage (%SPT), respiratory arousal index, and respiratory disorder index in 2 profiles. Conclusion The proposed data integration strategy successfully identified multiple significant OSA indicators.

Using the environmental justice approach to evaluate equitable allocation of urban parks: A case study of main urban area of Nanjing, China

Urban parks have broad benefits in promoting public health of urban residents and advancing urban sustainable development. The equity of urban park spatial allocation has a great significance for maintaining environmental justice. However, the current researches on the equity of urban park spatial allocation still focus on the quantity and geographical equality but pay less attention on the equity of quality and accessibility of spatial allocation. Based on the approach of environmental justice, with the main urban area of Nanjing as an example, we comprehensively analyzed the equity pattern of urban park spatial allocation from the three dimensions (six parameters), including park accessibility, area and quality. Integrated analysis methods were adopted, including internet map service for accessibility analysis, subjective and objective comprehensive quality evaluation, spatial autocorrelation and non-parametric test. The results showed that the spatial allocation pattern of urban parks in the study area had obvious core-edge characteristics. There was a certain degree of inequity in park accessibility, area and quality, with a relatively significant pattern of environmental injustice. There were significant differences in the inequity of six parameters in the three dimensions, with the accessibility score and accessible park area showing the most prominent inequity. The minimum time required to reach the park and the quality of the nearest urban park took the second place in inequity. The quantity of high-quality urban park and minimum time required to reach the high-quality urban park showed relatively small difference. The average values of accessibility score, total area and quality of urban parks accessible to high-income communities were 3.7, 2.7, and 1.6 times that of low-income communities, respectively. The results indicated that high-income communities enjoyed better accessibility, larger area and higher quality in terms of urban parks. Middle-income communities enjoyed the most prominent advantage of green space, while most low-income communities were unable to reach a high-quality urban park within 30 min's walk. Our results could provide a decision-making basis and planning reference for the optimal configuration and rational planning of urban parks in China.

Smart bibliometrics: an integrated method of science mapping and bibliometric analysis

Smart bibliometrics: an integrated method of science mapping and bibliometric analysis

Integrated geographical environment factors explaining forest landscape changes in Luoning County in the middle reaches of the Yiluo River watershed, China

Analysis of forest landscape changes and its driving factors is vital to forest ecosystem management and sustainable development. However, it is difficult to integrate various environment factors and explain the change of forest landscape. Research on the impact of integrate geographical environment factors on forest landscape changes is still lacking. In this study, we quantified forest area and mapped forest landscape distribution in 1990, 1995, 2000, 2005, 2000, 2010, and 2015 in Luoning County in the middle of the Yiluo River watershed by using multi-temporal land use data, and detected spatio-temporal changes of the forest landscape. Three types of forest landscape changes (unconverted, reforestation, and deforestation) and ten geographical environment factors (elevation, slope, proximity to previous forest edge, distance to rivers, mean annual temperature, mean annual precipitation, distance to roads, distance to residential centers, population density, Gross Domestic Product) were identified. Pearson correlation analysis and line regression analysis were applied to examine the relationships between forest landscape changes and geographical environment factors. Based on the relationships, correlation coefficient and adjusted R2, these environment factors were formed into an integrated geographical environment factors index (IGEF), and an approach for analyzing forest landscape changes along the geographical environment factors gradient was proposed. The results showed that: (1) the total area of forest landscape decreased from 1990 to 2000 and continued to increase from 2000 to 2015; (2) reforestation and deforestation were closely related to individual geographical environment factors and IGEF index; (3) reforestation and deforestation mainly occurred in the areas with low and medium IGEF index values, while forest landscape unconverted was mainly distributed in the areas with high and medium IGEF index values. The observed forest landscape changes could be explained by a set of given geographical environmental factors. Our findings are expected to enhance the understanding of integrated analysis method of geographical environmental factors and contribute to the targeted forest landscape management in mountain areas.

A new approach for selecting the most suitable oilseed for biodiesel production; the integrated AHP-TOPSIS method

The rapid growth of the world's population and industrial revolution has led to an increase in the need for energy. However, the scarcity of fossil fuels and serious environmental pollution problems have attracted researchers on developing alternative or renewable energy sources. Among these energy sources, biodiesel has been the most popular energy source for decades. Energy crops that are cultivated as oil feedstock such as soybean, cottonseed, rapeseed, and camelina for biodiesel production in Turkey. Due to different physicochemical properties of these oilseeds, fuel quality, engine performance characteristics and emission results of biodiesel are the significant criteria that have been changing. Therefore, these criteria were evaluated by using multi-criteria decision making (MCDM) techniques for the selection of the most suitable energy crop. For this purpose, AHP has been applied for evaluating the significance of each criterion and ranks of investigated alternatives have been calculated by using TOPSIS. The results identified rapeseed as the most suitable oilseed as an energy crop for cultivation in Turkey whereas cottonseed was an unsuitable choice for biodiesel production. This integrated analysis method here can be utilized by policymakers as a pre-investment tool in developing new business models for the goal of reducing exhaust emissions as well as decreasing dependence on fossil fuels.

Establishment of Integrated Analysis Method for Probing and Reconstructing Hydrogenation Mechanism of a Model Reaction

The hydrogenation of 4-nitrophenol (4-NP) has attracted much attention, since it is typically used as a model reaction for evaluating newly developed catalysts, but its mechanism is still debated. Herein, Co(OH)2-modified CuO catalyst (Co(OH)2/CuO) was used for the reduction of 4-NP to 4-aminophenol (4-AP) in an aqueous sodium borohydride (NaBH4) solution. The reaction mechanism was investigated by UV-Vis spectroscopy (UV-Vis), high-performance liquid chromatography (HPLC), HPLC-Q-orbitrap high-resolution mass spectrometry (LC-MS/MS), and 1HNMR spectroscopy (1HNMR) as an integrated technology at different concentrations of NaBH4. Samples were taken at specified time intervals and monitored using UV-Vis, HPLC, LC-MS/MS, and 1HNMR. With the help of comprehensive analysis, eight intermediates, including azo and azoxy compounds, were effectively captured, and the variation tendency of each intermediate was determined, revealing that the hydrogenation of 4-NP proceeds via a coexistence of the direct and condensation routes. The integrated analysis methods were powerful technical supports for the study of the catalysis mechanism.

Verification of analytical antiderivatives forms using correlation analysis for mechanical problems

An analytical search for antiderivative functions (indefinite integrals) is widely used in the mathematical simulation of various engineering, economic, ecological, biological, social, and other processes. In their turn, mechanical problems have many subproblems whose solution involves analytical integration methods. Among these problems is the problem of development of analytical models for navigation and ballistics support and control theory models in space rocket engineering. The advantage of this approach to mathematical simulation is a fast analysis of the state of dynamic systems on different time intervals without calculating all previous states. In their turn, for some classes of functions, antiderivatives may be found in several different ways, as a result of which there exist several different forms of antiderivatives that are hard to verify by the classical method in standard form. This is mainly due to the choice of various combinations of integration methods used in the development of analytical models, in particular in problems of applied mechanics. Taking into consideration these difficulties in the verification of the set of antiderivative functions, this paper proposes a method to check their analytical forms for correspondence with the use of correlation analysis. In doing so, the arrays of the values of each antiderivative form at certain nodal points are represented as a set of random variables. With this in mind, it is suggested that the verification process be conducted with the use of the standard approach based on correlation analysis (using Pearson’s correlation coefficient). The efficiency of the method is shown by the example of verifying the antiderivatives of the reciprocal of a squared quadratic trinomial. This approach will make it possible to check the adequacy of the i-th candidate antiderivative and to adapt the problem to the standard form.

ELOVL2-AS1 inhibits migration of triple negative breast cancer.

In this study, we identified a key enhancer RNA (eRNA) region in breast cancer (BRCA) by applying an integrated analysis method. Reported eRNA region and genes affected by them were selected as presumed target pairs. Kaplan–Meier (KM) survival and correlation analyses were performed to screen valuable eRNA region. Based on the KM value and its correlation with the paired target genes, we carefully selected ELOVL2-AS1 as a potential key eRNA region in BRCA. Subsequently, we analyzed the expression of ELOVL2-AS1 and ELOVL2 in four BRCA subtypes and in different BRCA cell lines. The expression of ELOVL2-AS1 and ELOVL2 in triple negative breast cancer (TNBC) was significantly lower than those in Luminal A. After that, we analyzed the function of genes that are positively correlated with ELOVL2-AS1. We found that the co-expression gene mainly related to cilia and cilia characteristics of TNBC is significantly weaker than that of Luminal A. Considering the stronger invasion and metastasis of TNBC (compared with Luminal A) and the close relationship between decreased cilia and metastasis, we overexpressed ELOVL2-AS1 in TNBC and observed its effect on cell migration. The results show that it can inhibit the migration of TNBC. Finally, we analyzed the assay for transposase-accessible chromatin sequencing data, chromatin interaction analysis with paired-end tag sequencing data, and chromatin immunoprecipitation sequencing data and identified the chromatin interaction between ELOVL2-AS1 and ELOVL2, suggesting a direct regulatory interaction.

Удельные затраты энергии поездов с асинхронным электроприводом

Objective: The assessment of energy effectiveness of traction drives for carriages of rolling stock models 81-765/766/767 and 81-556/557/558 (“NEVA”) from various producers and drafting technical requirements for drive electric equipment. Stock 81-765/766/767 uses asynchronous engine of 170 kW wattage and 43 Hz field rated frequency, 81-556/557/558 — 167 kW with 70 Hz rated frequency. Methods: The comparative analysis of drive energy indicators of trains with asynchronous electric drives has been accomplished in accordance with the calculation methodology. Measuring section was set in accordance with GOST P 50850-96. There are defined the assumptions at motion of rolling stock with equal maximal acceleration in a runaway and maximal deceleration in a braking and constant deceleration in a run-out. Maximal acceleration and deceleration were calculated incompliance adhesion set coefficient, grip weight (mass of motor cars) and moment of inertia. The calculation by method of analytical integration of motion differential equation was held on runaway five intervals. Initial technical data of trains with rated load as well as calculated indicators at train motion on measuring section were accepted. Diagrams of train motion on section were built and comparative analysis of characteristics of stock carriage models 81-765/766/767 and 81-556/557/558 (“NEVA”) was pursued. Results: It was established during the comparison that engine overload by torque on shaft is the same with 1.5 coefficient to rated torque. Stocks have significantly different indicators as by unit expenses as well as by motion dynamics. It’s been also established that for to minimize energy costs for traction it’s required to develop maximally allowable deceleration at braking and maximally allowable acceleration at runaway. Practical importance: The necessity of entry into Technical Task for new rolling stock of the requirement on stock check on runaway possibility with maximal set acceleration.

Similarity Analysis: Revealing the Regional Difference in Geomorphic Development in Areas with High and Coarse Sediment Yield of the Loess Plateau in China

The development of loess landforms is controlled by underlying, pre-existing paleotopography. Previous studies have focused on the inheritance of loess landform and the control of underlying paleotopography on modern terrain based on the digital elevation model (DEM), while the similarities and differences between modern terrain and underlying paleotophotography have not been directly spatialized. In this study, areas with high and coarse sediment yield (AHCSY) in the Loess Plateau of China were selected to form the study area, and the DEM of the study area’s underlying paleotophotography was reconstructed using detailed geological maps, loess thickness maps, and underlying paleotopographic information. The hypsometric integral (HI) and spatial similarity analysis methods were used to compare the spatialized difference between underlying and modern terrain of the Loess Plateau from the perspectives of the landform development stage and surface elevation, respectively. The results of the HI method demonstrate that essentially, there are similarities between the geomorphologic development stages of underlying and modern terrain, and only some local differences exist in some special areas. The results regarding the spatialized coefficient of relative difference and the Jensen–Shannon divergence demonstrate that the thicker the loess is, the weaker the similarity is, and vice versa. Meanwhile, according to the present loess landform division, the order of regional similarity from low to high is as follows: loess tableland, broken loess tableland, hilly regions, dunes, and the Yellow River Trunk. The use of the similarity analysis method to analyze similarities between underlying and modern terrain plays an important role in revealing the inheritance of loess landforms.

Spherical solidification: An application of the integral methods

In this paper we developed and applied the simple and double integral methods to solve phase-change problems. We performed the double integral method considering a linear temperature profile applied to spherical geometry, thus obtaining an analytical solution for the solidification time, a novelty for this type of problem. The methods were evaluated considering different solidification conditions with finite and infinite Biot numbers (∞; 2, 5 and 10) and Stefan numbers (0.0061; 0,01). The results were compared against published data, and the performance between the linear analytical double integral method (DIM) and simple integral method (SIM) methods were compared against the computational quadratic SIM of Milanez and Ismail (1984). These results were further compared against our implemented computational quadratic DIM. Hitherto, similar comparisons have been neglected in the literature. Overall, the results indicated that both methods were capable of reproducing the physics of solidification. However, the linear double integral method achieved better agreement in terms of solidification time against the published data. The reduction in numerical error in computing the solidification time using the linear double integral method was up to 84.61% compared to the simple integral (for Bi = 2 and Ste = 0.01). For the infinite condition, the quadratic SIM in the literature did not present improvements against the analytical linear DIM. In general, for a Bi = 2 the analytical linear DIM and the quadratic DIM are equivalent. For higher Stefan and Biot numbers the computational quadratic methods are more accurate due to the inclusion of the Stefan number in the temperature coefficients. This study attested to the correctness of the mathematical development using the linear temperature profile in conjunction with the double integral method for solving the solidification process in spheres. This study can be extended in future work to the solidification of different material.

An in silico and in vitro integrated analysis method to reveal the curative mechanisms and pharmacodynamic substances of Bufei granule on chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a common respiratory disease with high disability and mortality. Clinical studies have shown that the Traditional Chinese Medicine Bufei Granule (BFG) has conspicuous effects on relieving cough and improving lung function in patients with COPD and has a reliable effect on the treatment of COPD, whereas the therapeutic mechanism is vague. In the present study, the latent bronchodilators and mechanism of BFG in the treatment of COPD were discussed through the method of network pharmacology. Then, the molecular docking and molecular dynamics simulation were performed to calculate the binding efficacy of corresponding compounds in BFG to muscarinic receptor. Finally, the effects of BFG on bronchial smooth muscle were validated by in vitro experiments. The network pharmacology results manifested the anti-COPD effect of BFG was mainly realized via restraining airway smooth muscle contraction, activating cAMP pathways and relieving oxidative stress. The results of molecular docking and molecular dynamics simulation showed alpinetin could bind to cholinergic receptor muscarinic 3. The in vitro experiment verified both BFG and alpinetin could inhibit the levels of CHRM3 and acetylcholine and could be potential bronchodilators for treating COPD. This study provides an integrating network pharmacology method for understanding the therapeutic mechanisms of traditional Chinese medicine, as well as a new strategy for developing natural medicines for treating COPD.

Man-Machine Modeling and Safety Analysis Method for Landing Process Based on SysML and Simulink

The large-scale system’s mission process and the interaction within the system are becoming more complex with the improvement of the integration and intelligence, and the complex interactions among multiple factors, such as the unsafe behavior of personnel, equipment failures, and environmental interference, make safety analysis a greater challenge. Aimed at the safety of carrier aircraft, an integrated system modeling and safety analysis method for aircraft landing process were proposed based on System Modeling Language (SysML) and Simulink. First, the SysML models were built according to the analysis of the mission process, including system structure and behavior process, using multiple diagrams. Second, the SysML models were transformed into and integrated with the Simulink platform to build entity models with continuous dynamic characteristics and to perform safety analysis through simulation. Finally, an example of aircraft attitude control during landing was given to demonstrate the proposed method, and the safety states were analyzed and assessed under different disturbance conditions.

Permeate Flux in Ultrafiltration Processes-Understandings and Misunderstandings.

Concentration polarization refers to the rapid emergence of concentration gradients at a membrane/solution interface resulting from selective transfer through the membrane. It is distinguishable from fouling in at least two ways: (1) the state of the molecules involved (in solution for concentration polarization, although no longer in solution for fouling); and (2) by the timescale, normally less than a minute for concentration polarization, although generally at least two or more orders of magnitude more for fouling. Thus the phenomenon of flux decline occurring over a timescale of tens of minutes should not be attributed to concentration polarization establishing itself. This distinction and a number of questions surrounding modelling are addressed and clarified. There are two paradigmatic approaches for modelling flux, one uses the overall driving force (in which case allowance for osmotic effects are expressed as additional resistances) and the other uses the net driving force across the separating layer or fouled separating layer, although often the two are unfortunately comingled. In the discussion of flux decline models’ robust approaches for the determination of flux-time relationships, including the integral method of fouling analysis, are discussed and various concepts clarified. The final section emphases that for design purposes, pilot plant data are vital.

Compressive Strength Estimation and CO2 Reduction Design of Fly Ash Composite Concrete

Fly ash is broadly utilized to produce concrete materials. This study presents a strength estimation model and a CO2 reduction design method for concrete with fly ash. First, a hydration-based strength (HBS) model is proposed for the evaluation of strength development at different ages of fly ash composite concrete with different mix proportions. Second, CO2 emissions for 1 MPa strength were evaluated. The analysis results show that, as the fly ash-to-binder ratio (FA/B) increased, the CO2 emissions for 1 MPa strength decreased. For concrete with a low water-to-binder ratio (W/B), the addition of high content of fly ash had an obvious dilution effect, which increased the reaction degree of cement and reduced CO2 emissions for 1 MPa strength. Moreover, the extension of the design age could reduce CO2 emissions for 1 MPa strength. Third, a genetic-algorithm-based optimal design model is proposed to find the individual mass of cement and fly ash of low-CO2 concrete. The analysis results show that, as the water contents increased from 160 to 170 kg/m3, to obtain the same strength, cement mass and fly ash mass increased, while the water/binder ratio and fly ash/binder ratio did not change. This means that the reduction in mixed water is one feasible way to lower CO2 emissions. In summary, the proposed strength–emission integrated analysis method is useful for designing sustainable fly ash composite concrete with the desired strength and low levels of CO2 emissions.

Assessment of Risks and Threats of "Green" Entrepreneurship based on Cross-Factor Modeling

The article is a continuation of a number of scientifc studies conducted by the authors within the framework of government assignments and grants, dedicated to identifying the relationship between the economic security of territories and the development of "green" entrepreneurship on them.Purpose: of the study is to model the assessment of the state of economic security of territories under various conditions of the transition to "green" entrepreneurship, taking into account the action of external and internal factors. "Green" entrepreneurship is a priority area for the development of Russian regions, consistent with the achievement of Russia's national strategic goals for the period up to 2030.Methods: in this work, cross-factor modeling and the method of integral analysis are used to calculate the composite index of the state of economic security and its structural components, taking into account the development of "green" entrepreneurship, supplemented by the method of a priori ranking of factors to assess the contribution of each component and justify the priority the selected factors affecting the level of economic security of the regions.Results: a three-component cross-factor model for assessing the state of economic security in certain regions of the Russian Federation (Moscow Region, Leningrad Region, Sverdlovsk Region, Novosibirsk Region, Altai Territory, Krasnodar Territory) had been calculated and tested. The regions were ranked according to the value of each of the components, as well as separately according to the aggregate level of economic security. The necessity of stimulating the development of "green" entrepreneurship in each of the analyzed regions. Have been substantiated and stimulating and discouraging factors that have an impact on the level of economic security, taking into account "green" entrepreneurship, pointwise in each subject, have been identifed.Conclusions and Relevance: the proposed approach to assessing the impact of the identifed factors on the level of economic security of the regions, taking into account the development of "green" entrepreneurship on the basis of the developed cross-factor model, made it possible to build a rating of territories and identify stimulating and discouraging factors in their development. On the basis of which to determine the tools for influencing the economic security in a separate entity.

Improved Thermoeconomic Energy Efficiency Analysis for Integrated Energy Systems

The structure of an integrated energy system is complex. Thermoeconomics can play a significant role in the analysis of IES because it makes up for the deficiency of traditional thermodynamic analysis and provides new information on the cost and energy conversion efficiency. When using thermoeconomics to analyze the energy efficiency of an IES, one key issue that needs to be solved is how to transfer irreversible loss across thermal cycles, so that the mechanism of system performance degradation can be fully revealed. To this end, an irreversible cost and exergy cost integrated analysis method based on improved thermoeconomics is proposed, in which the cumulative and transmission impact of irreversible loss across thermal cycles is evaluated using linear transformation of &lt;KP&gt; matrix. A case study on a 389MW combined cooling, heating, and power IES demonstrates the effectiveness of the proposed approach. The proposed approach can reveal the key links impairing the overall energy efficiency and transfer of irreversible loss across thermal cycles. The approach can be extended to various types of IES to provide directions for the assessment and optimization of the system.