Time Series Plots Research Articles

Collection, Analysis, and Reporting of Kentucky Traffic Incident Management Performance

Traffic incidents remain all too common. They negatively affect the safety of the traveling public and emergency responders and cause significant traffic delays. Congestion associated with incidents can instigate secondary crashes, exacerbating safety risks and economic costs. Traffic incident management (TIM) provides an effective approach for managing highway incidents and reducing their occurrence and impacts. The paper discusses the establishment and methods of calculation for five TIM performance measures that are used by the Kentucky Transportation Cabinet (KYTC) to improve incident response. The measures are: roadway clearance time, incident clearance time, secondary crashes, first responder vehicle crashes, and commercial motor vehicle crashes. Ongoing tracking and analysis of these metrics aid the KYTC in its efforts to comprehensively evaluate its TIM program and make continuous improvements. As part of this effort, a fully interactive TIM dashboard was developed using the Microsoft Power BI platform. Dashboard users can apply various spatial and temporal filters to identify trends at the state, district, county, and agency level. The dashboard also supports dynamic visualizations such as time-series plots and choropleth maps. With the TIM dashboard in place, KYTC personnel, as well as staff at other transportation agencies, can identify the strengths and weaknesses of their incident management strategies and revise practices accordingly.

Caputo SIR model for COVID-19 under optimized fractional order

Everyone is talking about coronavirus from the last couple of months due to its exponential spread throughout the globe. Lives have become paralyzed, and as many as 180 countries have been so far affected with 928,287 (14 September 2020) deaths within a couple of months. Ironically, 29,185,779 are still active cases. Having seen such a drastic situation, a relatively simple epidemiological SIR model with Caputo derivative is suggested unlike more sophisticated models being proposed nowadays in the current literature. The major aim of the present research study is to look for possibilities and extents to which the SIR model fits the real data for the cases chosen from 1 April to 15 March 2020, Pakistan. To further analyze qualitative behavior of the Caputo SIR model, uniqueness conditions under the Banach contraction principle are discussed and stability analysis with basic reproduction number is investigated using Ulam–Hyers and its generalized version. The best parameters have been obtained via the nonlinear least-squares curve fitting technique. The infectious compartment of the Caputo SIR model fits the real data better than the classical version of the SIR model (Brauer et al. in Mathematical Models in Epidemiology 2019). Average absolute relative error under the Caputo operator is about 48% smaller than the one obtained in the classical case (nu =1). Time series and 3D contour plots offer social distancing to be the most effective measure to control the epidemic.

A Stochastic Multi-Criteria Decision-Making Algorithm for Dynamic Load Prioritization in Grid-Interactive Efficient Buildings

Abstract Increasing deployment of advanced sensing, controls, and communication infrastructure enables buildings to provide services to the power grid, leading to the concept of grid-interactive efficient buildings. Since occupant activities and preferences primarily drive the availability and operational flexibility of building devices, there is a critical need to develop occupant-centric approaches that prioritize devices for providing grid services, while maintaining the desired end-use quality of service. In this paper, we present a decision-making framework that facilitates a building owner/operator to effectively prioritize loads for curtailment service under uncertainties, while minimizing any adverse impact on the occupants. The proposed framework uses a stochastic (Markov) model to represent the probabilistic behavior of device usage from power consumption data, and a load prioritization algorithm that dynamically ranks building loads using a stochastic multi-criteria decision-making algorithm. The proposed load prioritization framework is illustrated via numerical simulations in a residential building use-case, including plug-loads, air-conditioners, and plug-in electric vehicle chargers, in the context of load curtailment as a grid service. Suitable metrics are proposed to evaluate the closed-loop performance of the proposed prioritization algorithm under various scenarios and design choices. Scalability of the proposed algorithm is established via computational analysis, while time-series plots are used for intuitive explanation of the ranking choices.

Modeling of measles epidemic with optimized fractional order under Caputo differential operator

Abstract Memory is an important characteristic of an epidemic. One of such memory dependent and highly contagious viral diseases is measles that is also responsible for more than 140,000 deaths in 2018 in various regions of Asia and Africa. In order to better understand the transmission dynamics of measles, we have developed a new epidemiological model while considering both integer and fractional order operators and presented comparison. The Caputo fractional model has a unique solution with the positively invariant region. On the basis of basic reproduction number R 0 , stability analysis is discussed and sensitivity of parameters is investigated using PRCC global technique. Not only parameters but fractional order χ is also optimized via nonlinear least-squares approach with availability of statistical data obtained from WHO. Various simulations in terms of time series plots, 3D meshes and contours are carried out to observe effects of parameters on dynamics of the epidemic wherein it is said to be persistent for χ → 0 demonstrating the role being played by Caputo fractional derivative towards measles dynamics.

Groundwater recharge quantification using multiproxy approaches in the agrarian region of Bundelkhand, central India

The Bundelkhand region is one of the most important agricultural regions in central India, where increasing water demand has put tremendous pressure on groundwater resources. The groundwater is the primary source for domestic, agricultural and industrial purposes in the Bundelkhand region. Here, we focus on the Jhansi district, located in the Bundelkhand region. The study area comes under the semi-arid zone and facing a variable climate condition that has been worsened due to the irregular rainfall. We have compiled numerous datasets such as; depth to water level record, rainfall, surface and subsurface water structures and satellite imagery from various sources. We have prepared spatial plots of groundwater levels using depth to water level data for 1996 and 2016. We have observed marked spatial variation in depth to water level maps during pre- and post-monsoon of 1996 and 2016. The time-series plot of groundwater levels shows both declining and rising trends between 1996 and 2016. We have also estimated groundwater abstraction and recharge during 2016 and correlated them with land use and land cover (LULC) activities and lithological units of the study area. The estimated net groundwater abstraction is about 50943 ha m (ham) during 2016; show marked spatial variation. The estimated recharge for the Jhansi district is about 73464 ham during 2016, of which 63% is from irrigation return flow due to groundwater pumping, 17% from irrigation return due to surface water structures, and remaining from seepage from canal and surface water structures. Our results suggest that the groundwater recharge and abstraction are directly linked to the LULC and lithological units. In addition, results obtained from the present study suggest a ‘safe’ category of groundwater development stage for the Jhansi district during 2016, except for Mauranipur and Bangra blocks. Our results can also be useful for better groundwater resource development and sustainable management.

A Bayesian test for the 4.2 ka BP abrupt climatic change event in southeast Europe and southwest Asia using structural time series analysis of paleoclimate data

It has been proposed that there was an abrupt climatic change event around 4.2 ka BP that affected societies and even has been linked to the collapse of empires. Subsequent studies have reached conclusions that both support and contradict the proposed event; yet nevertheless, 4.2 ka BP has now been adopted as the stratigraphic boundary point between the Middle and Upper Holocene. Time series plots of paleoclimate studies that claim to support the abrupt climate change hypothesis show differing temporal patterns so, in this study, we apply the Bayesian structural time series (BSTS) approach using the CausalImpact package to test data from southeast Europe and southwest Asia for which it is claimed that they demonstrate a climatic anomaly around 4.2 ka BP. To do this, each “affected” time series is synthetically reconstructed using “unaffected” series as predictors in a fully Bayesian framework by the BSTS method and then forecast beyond the assumed starting point of the event. A Bayesian hypothesis test is then applied to differences between each synthetic and real time series to test the impact of the event against the forecast data. While our results confirm that some studies cited in support of the 4.2 ka BP event hypothesis do indeed hold true, we also show that a number of other studies fail to demonstrate any credible effect. We observe spatial and data patterning in our results, and we speculate that this climatic deterioration may have been a consequence of an asymmetrical northward expansion or migration of the Northern Hemisphere Hadley cell. Furthermore, we observe that while the signals are generally not credible, types of proxy data from the Mesopotamia region and east are consistent with aeolian dust storms.

Impact of COVID-19 Pandemic on Stock Market Returns

The main purpose of the study is to examine the impact of COVID-19 pandemic on stock market returns. This study employed causal comparative research design which deals with how daily infected and death cases of COVID-19 effect on stock market returns. The study revealed that the changes on daily infected new cases have been severely inflected stock returns in overall as well as cross-over the stock markets. Whereas, the influence of death form COVID-19 found negative but mostly insignificant. The categorical variables size of stock market impact found very low. The empirical evidences were examined using time series plot and regression model. The study period has covered 100 days after COVID-19 infected cases identified in sampled countries, considering 30 nations.

Effectiveness of peer to peer strategy in reducing accidents and injuries at a selected platinum mine in Zimbabwe

The selected mining company implemented the "Peer to Peer" strategy in 2008 to fast track achievement of zero tolerance to injuries and fatalities incidents at its workplace. Our study, therefore, sought to assess the effectiveness of this strategy in reducing accidents and injuries at this selected platinum mine in Zimbabwe. A mixed-method cross-sectional survey was conducted on 32-day shift employees using a semi-structured questionnaire with closed and open-ended questions. Furthermore, incident trend analysis was done on data obtained from the records from 2004 to 2017. Covert observations were then employed to triangulate findings from data collected using the questionnaire on practices. The tests Hotelling, Chi-square, time series plots, and Multiple Logistic Regressions were employed to compare the variables of interest before and after implementing the peer to peer strategy. There was a significant drop in the number of incidents after implementing the peer to peer strategy. There was no association between tested demographic characteristics and the level of employees' knowledge of the strategy. Employees were afraid to implement the strategy to their superiors fully. Findings pointed out that this strategy was effective despite being part of a cocktail of strategies. There was a vast decrease in the rate of occurrence of incidents after the implementation of this strategy. However, there is a need for engagement to address the subordinate management dynamics that was observed to be a threat in the comprehensive implementation of this strategy.

Chaotic Oscillation of Satellite due to Aerodynamic Torque

This study presents the chaotic oscillation of the satellite around the Earth due to aerodynamic torque. The orbital plane of the satellite concurs is same as the tropical plane of Earth. The half-width of riotous separatrix is assessed utilizing Chirikov’s measure. Variety of boundary techniques shows that streamlined force boundary (ɛ), unpredictability of circle (e), and mass-proportion (ω0) convert normal wavering to the disorganized one. We studied the behavior of trajectories due to change in parameters with Lyapunov exponents and time series plots. The theory is applied to Resourcesat-1, an artificial satellite of the Earth.

The Tensile Behaviour of Highly Filled High-Density Polyethylene Quaternary Composites: Weld-Line Effects, DIC Curiosities and Shifted Deformation Mechanisms.

The interactive effects between additives and weld lines, which are frequent injection-moulding defects, were studied in high-density polyethylene (HDPE) and compared to weld-line-free reference samples. These materials were formulated around a D- and I-optimal experimental design, based on a quadratic Scheffé polynomial model, with up to 60 wt% calcium carbonate, masterbatched carbon black and a stabiliser package. Where reasonable and appropriate, the behaviours of the systems were modelled using statistical techniques, for a better understanding of the underlying trends. The characterisations were performed through the use of conventional tensile testing, digital image correlation (DIC) and scanning electron microscopy (SEM). A range of complex interactive effects were found during conventional tensile testing, with DIC used to better understand and explain these effects. SEM is used to better understand the failure mechanics of some of these systems through fractography, particularly regarding particle effects. A measure is introduced to quantify the deviation of the pre-yield deformation curve from the ideal elastic case. Novel analysis of DIC results is proposed, through the use of combined time-series plots and measures quantifying the extent and localisation of peak deformation. Through this, it could be found that strong shifts in the deformation mechanisms occur as a function of formulation and the presence/absence of weld lines. Primarily, changes are noted in the onset of continuous inter- and intralamellar slip and cavitation/fibrillation, seen through the onset of localised deformation and stress-whitening.

Analysisian Analysis of the Impact of SME Financing on Economic Growth in Zimbabwe (2015-2019)

Small and Medium scale Enterprises (SMEs) are important for successful economic growth and social development. There is a global increasing recognition of the importance of Small and Medium Scale Enterprises in terms of supporting overall economic growth and development. The primary purpose of the study was to assess the contribution of SMEs financing towards economic growth for Zimbabwe. Specifically, the study investigated the impact of SMEs financing on GDP growth, Job Creation, Poverty Datum Line, and Revenue Generation. The study focused on the classical and the modern theories mainly the Neoclassical Growth Theory, Finance-Growth Theory, Lending theory, Signaling theory, the pecking order theory and the Access to finance Theory of Change. This study adopted the positivism research paradigm and an explanatory correlational study design since it helped the researcher to comprehend and describe how SME Financing drives economic growth. In this study all registered SMEs who received loans from all commercial banks in Zimbabwe since 2015 represented the entire target population. The SMEs sector was selected due to its importance in Zimbabwe achieving the economic pillar of Vision 2030. The data gathered was presented and analyzed in a way that enabled statistical inferences to be made. Statistical methods of presentation such as time series plots, descriptive statistic tables, Correlograms and Multiple Linear regression model were used to aid comparability and ensure meaningful interpretation. Tests were performed on sample data to ensure that required conditions were met before regression modelling. The model was fitted using Eviews 10 statistical data analysis package. In a correlational study, the researcher examined whether and to what degree a statistical relationship exists between SMEs financing and Economic Growth. This study employed Classical Linear Regression Model (CLRM) to ascertain the statistical relationship between SMEs financing and Economic Growth. To evaluate the appropriateness and validity of the model the study analyzed the properties of the statistical distribution of the residuals generated by the fitted model to check for autocorrelation, heteroscedasticity and normality. The overall significance of the model was also evaluated by inspecting the model’s coefficient of determination (R-squared) and the probability value for the F-statistic. The estimated models found SMEs financing to have a significant positive effect on Economic Growth with respect to GDP Growth and Revenue generation through Tax Formation. However, it was revealed that SMEs Financing has no significant effect on changes in the movement of the Poverty Datum Line. It was also revealed that SMEs financing has failed to stimulate job creation in Zimbabwe due to continued rise in unemployment levels coupled by closure of large corporates. Greater efforts should be made to make available, short, medium and long term loans to productive investments like SMEs as they constitute an integral part of the growth and transformation process of an agro-based economy like that of Zimbabwe. The central Bank of Zimbabwe (RBZ) should ensure that all the SMEs keeps appropriate records of what is required by banks for extension of their credits to individuals. More so, the Reserve Bank of Zimbabwe should strengthen its monetary policy tools in order to stabilize costs of doing business and lending cost. Future studies should therefore consider also investigating the impact of both private equity and public sector investment on economic growth in order to get an exhaustive picture on the implications of financing SMEs, Private Equity firms and publicly listed firms on economic development.

Comparison of detection limits estimated using single- and multi-concentration spike-based and blank-based procedures

Spike- and blank-based procedures were applied to estimate the detection limits (DLs) for example analytes from inorganic and organic methods for water samples to compare with the U.S. Environmental Protection Agency's (EPA) Method Detection Limit (MDL) procedures (revisions 1.11 and 2.0). The multi-concentration spike-based procedures ASTM Within-laboratory Critical Level (DQCALC) and EPA's Lowest Concentration Minimum Reporting Level were compared in one application, with DQCALC further applied to many methods. The blank-based DLs, MDLb99 (99th percentile) or MDLbY (= mean blank concentration + s × t), estimated using large numbers (>100) of blank samples often provide DLs that better approach or achieve the desired ≤1% false positive risk level compared to spike-based DLs. For primarily organic methods that do not provide many uncensored blank results, spike-based DQCALC or MDL rev. 2.0 are needed to simulate the blank distribution and estimate the DL. DQCALC is especially useful for estimating DLs for multi-analyte methods having very different analyte response characteristics. Time series plots of DLs estimated using different procedures reveal that DLs are dependent on the applied procedure, should not be expected to be static over time, and seem best viewed as falling over a range versus being a single value. Use of both blank- and spike-based DL procedures help inform this DL range. Data reporting conventions that censor data at a threshold and report “less than” that threshold concentration as the reporting level have unknown and potentially high false negative risk. The U.S. Geological Survey National Water Quality Laboratory's Laboratory Reporting Level (LRL) convention (applied primarily to organic methods) attempts to simultaneously minimize both the false positive and false negative risk when <LRL is reported and data between DL and the higher LRL are allowed to be reported.

Extreme multistability in a fractional-order thin magnetostrictive actuator (TMA)

In this paper, we consider and investigate the dynamics of a fractional-order thin magnetostrictive actuato with quintic nonlinearity. The energy balance method is used to establish the motion equation of the system. Numerical solutions of the system are studied using the Caputo method and Adams Bashforth Moulton scheme. In order to analyze the dynamical behaviors of the proposed system, some mathematical tools including bifurcation diagrams, Lyapunov exponents, two-parameter bifurcation diagrams, time series plots and phase portraits are exploited. The bifurcation diagrams show that the system under consideration exhibits rich and intriguing behaviors including period-doubling route to chaos, complex phase space trajectory and extreme multistability. One of the most novelty of the proposed system is that its exhibits extreme multistability, which was not yet reported in the existing thin magnetostrictive actuators discussed in the literature to the author’s knowledge. The results carried out in this work may help us in better understanding of the thin magnetostrictive actuators.

A Numerical and Analytical Study of Phase Synchronization in Coupled SC-CNN Based Non-Identical Chaotic Systems

This paper seeks to address the phase synchronization phenomenon using the drive-response concept, in our proposed model, State Controlled Cellular Neural Network (SC-CNN) based on variant of MuraliLakshmanan-Chua (MLCV) circuit. Using this unidirectionally coupled chaotic non autonomous circuits, we described the transition of unsynchronous to synchronous state, by numerical simulation method as well as the results are confirmed by solving explicit analytical solution. In this aspect, the system undergoes the new effect of phase synchronization (PS) phenomenon have been observed before complete synchronization (CS) state. To characterize these phenomena by the phase portraits and the time series plots. Also particularly characterize for PS by the method of partial Poincare section map using phase difference versus time, numerically and analytically. The study of dynamics involved in SC-CNN circuit systems, mainly applicable in the field of neurosciences and in telecommunication fields.

The Nexus Among Non-performing Loans, Lending Rates and Financial Performance of Banks in Ghana

The main purpose of the study was to examine the relationship among non-performing loans, Commercial Banks’ lending rate and financial performance of Commercial Banks in Ghana. The time series design was used along with the quantitative research approach. Secondary data on the selected variable and some control variables were accessed from the economic and monetary data base of the Central Bank of Ghana from 2006 to 2019 and used for the analysis. Both theoretical and empirical literature was reviewed to create a research gap for the study. Time series properties of the variables such stationarity and descriptive were done to assess the stability of the time series variables. The Augmented Dickey-Fuller unit-root test was used for the stationarity test since the time series plots indicated no possibility of serious structural breaks. Return on assets before tax, return on equity after tax, Commercial Banks interest rate, inflation and inter-banks interest rate were found to be significant determinants of Non-performing loans in the financial sector of Ghana. It was concluded that simultaneous relationships exist among the level of non-performing loans, Commercial Banks’ lending rate and financial performance of Banks in Ghana, hence anyone of them could serve as a lead variable or policy variable in ensuring a stable financial system in Ghana. It was recommended that the management of commercial banks must exploit other avenues of generating income such as direct project financing among others and reduce reliance on interest payment through increase in interest charges.

Analysis of short-term air quality monitoring data in a coastal area

&lt;abstract&gt; &lt;p&gt;Short-term air quality monitoring in a coastal area, Naklua Subdistrict, Pattaya, Thailand is an activity to support the designated area under Thailand's sustainable tourism development. This study provided a short-term monitoring data analysis on time series and Bivariate Polar Plot (BVP) to provide the status of air quality and to determine the potential source area of air pollution. The result showed that NO&lt;sub&gt;2&lt;/sub&gt;, SO&lt;sub&gt;2&lt;/sub&gt;, CO and PM&lt;sub&gt;10&lt;/sub&gt; were not higher than the national air quality standards, while the 24-hour average of PM&lt;sub&gt;2.5&lt;/sub&gt; and the 8-hour average of O&lt;sub&gt;3&lt;/sub&gt; were slightly higher than the World Health Organization (WHO) air quality guideline values. The nighttime PM&lt;sub&gt;2.5&lt;/sub&gt; concentration was higher than the daytime concentration, and its potential source area is urban areas in the south. However, the daytime O&lt;sub&gt;3&lt;/sub&gt; concentration is higher than the nighttime concentration. Its potential source area is from the northwest, where Sichang island is located. This result could be used to support air pollution management by controlling and reducing emissions in the potential source areas as the first priority. Also, the study revealed that the BVP technique could be used to determine the source area of air pollution in the coastal area, where wind circulation is more complex than that over the land.&lt;/p&gt; &lt;/abstract&gt;

Recurrence analysis of innovation behavior of bitcoin market agents in conditions of COVID-19

The relevance of the research subject is explained by a fundamental change in the conditions of existence and development of agents of the digital economy, limited knowledge about their behavior under conditions of quarantine restrictions. The aim of the research is to study the series of the dynamics of the price of bitcoin and the frequency of online requests for bitcoin as an indicator of the behavior of agents of the digital economy using the methods of qualitative recurrent analysis. The types of constructed time series plots of the price of bitcoin and the frequency of requests for bitcoin are defined as drift with a superimposed linearly gradually increasing sequence, which indicates the unpredictability of the behavior of digital economy agents with a gradual stabilization in new quality trend. The scientific novelty of the research results lies in the proven connection between the series of bitcoin price dynamics and the frequency of online requests for bitcoin, tracking changes in the behavior of digital economy agents before and after the introduction of quarantine restrictions. The procedure for conducting a qualitative recurrence analysis of the series of dynamics is generalized, which takes into account the specifics of the formation of the frequency of online requests for bitcoin, the price and the behavioral aspect of its formation. The practical value lies in defining the characterization of the behavior model of digital economy agents under conditions of quarantine restrictions. The behavior of digital economy agents in the context of COVID-2019 requires further research, in particular, using cross-recurrent analysis methods.

Microsynth: Synthetic Control Methods for Disaggregated and Micro-Level Data in R

The R package microsynth has been developed for implementation of the synthetic control methodology for comparative case studies involving micro- or meso-level data. The methodology implemented within microsynth is designed to assess the efficacy of a treatment or intervention within a well-defined geographic region that is itself a composite of several smaller regions (where data are available at the more granular level for comparison regions as well). The effect of the intervention on one or more time-varying outcomes is evaluated by determining a synthetic control region that resembles the treatment region across pre-intervention values of the outcome(s) and time-invariant covariates and that is a weighted composite of many untreated comparison regions. The microsynth procedure includes functionality that enables its user to (1) calculate weights for synthetic control, (2) tabulate results for statistical inferences, and (3) create time series plots of outcomes for treatment and synthetic control. In this article, microsynth is described in detail and its application is illustrated using data from a drug market intervention in Seattle, WA.

Hydrological Response of Land Use Land Cover Change on Stream Flow of Anger Watershed, Blue Nile Basin, Ethiopia

Stream flow of Anger watershed (7,982 km2), located in Western Oromia Regional State, Ethiopia was simulated by using soil and water assessment tool (SWAT) model. Assessment of layer staking, mosaicking, image classification and accuracy was carried by ArcGIS. The main target of this study was to determine the SWAT Model applicability and impact of past land-use land-cover change on stream flow of the Anger watershed. The time series data from 1990 to 1999 was used for model parameter calibration, and data from 2000 to 2004 were used to validate the model using the input parameter set. The performance of the SWAT model was evaluated by both R2 time series plots and ENS the statistical measures. The results of the model during calibration for monthly stream flow was R2= 0.90, ENS= 0.76 and during validation R2= 0.84, ENS= 0.63 respectively. Validation of image classification is achieved through Mosaicking image and Google Earth image. The performance of the Arc GIS model was evaluated by using the overall accuracy and kapa coefficient. The agreement between classified land use image and ground truth of the year 1986, 2000 and 2010 were showed a good agreement with result of overall accuracy=88%, 85% and 87% and kapa coefficient=81%, 79% and 82% respectively. Simulation of steam flow of the watershed under the impacts of past land-use land-cover changes can be determined by using SWAT model as a tool for water resources planning and management in this watershed.

Wavelet and Cross-Correlation Analysis of Relativistic Electron Flux with Sunspot Number, Solar Flux, and Solar Wind Parameters

The Geostationary Operational Environmental Satellites (GOES) have been monitoring the Earth's radiation environment and is providing the electron flux data (of energy &gt;0.8 MeV, &gt;2 MeV, and &gt;4 MeV) by means of a connected sensor subsystem. Relativistic electron flux is one of the components of the radiation belt which not only affects the electrical system in satellites but also has an impact on Earth’s upper atmospheric climatic variation. We have carried out a study to determine the relation of sunspot number (R), solar flux (F10.7), and solar wind parameters i.e., solar wind velocity (Vsw), plasma density Nsw), the southern component of the interplanetary magnetic field (IMF-Bz), Plasma temperature (Tsw) with relativistic electron flux of energy &gt;0.8 MeV, &gt;2 MeV, and &gt;4 MeV in outer radiation belt using the data of 24 years (1996-2020) covering solar cycle 23 and 24. Time series analysis, Cross-correlation and wavelet analysis techniques have been used in this study. The time series plot displayed that the radiation is occupied mostly by electron flux of energy less than 4 Mev and solar cycle 23 (1996-2008) was strong to produce more intensity of relativistic electron flux of all energy in comparison to cycle 24 (2008-2019). Results from cross-correlation analysis illustrated that Bz has no significant impact on the enhancement of relativistic electron flux of any energy range in the radiation belt. Whereas other studied parameters have a positive correlation with relativistic electron flux, but with significantly different coefficient values for different energy. We found that electron flux &gt;0.8 MeV and &gt;2 MeV has a strong positive association with sunspot number, solar flux, solar wind velocity, plasma density and temperature whereas weak correlation with electron flux of energy &gt;4 MeV. This result leads us to conclude that solar activity and solar parameters have greater influence in producing relativistic electron flux of energy ~ 0.8-4 MeV, than of flux &gt; 4 MeV. The study made to observe the distribution of relativistic electrons in radiation belt with time through continuous wavelet analysis showed that electron flux of energy &gt;0.8 has a higher periodicity in comparison to the flux of other energy ranger.