Analysis and Forecast of Railway Freight Volume based on Prophet-Deep AR Model

The research on railway freight volume forecast is of great significance to the allocation of railway freight transport resources, the formulation of transport plans and the organization of railway freight transport. This study, by fully mining the railway freight ticket data information, put forward the precise forecast model of railway freight volume under different types of freight. Firstly, the railway freight ticket data are cleaned, regulated and integrated, and the time series of the daily number of railway freight trains are constructed, get the trend, periodicity and holiday data of railway traffic data, and set the parameters of Chinese holidays and rest days according to the demand characteristics of different categories. Secondly, the forecasting result of the Prophet is taken as a cooperative parameter. DeepAR is used to forecast, and a combined model of the Prophet-DeepAR is constructed. Finally, the combined model was validated with Shanghai Railway Bureau data from January 1, 2015 to December 31, 2018 for the food and tobacco category, and with Prophet-DeepAR, LSTM, Wavelet, BILSTM, and Prophet-LSTM, prophet-wavelet and Prophet-Bilstm are used to compare the prediction results. The results show that the Prophet-DeepAR model can extract the multi-dimensional periodicity of freight traffic and mine the trend information of freight traffic, and get the prediction result with high precision. It has better accuracy than other models

Real-Time Building Management System Visual Anomaly Detection Using Heat Points Motion Analysis Machine Learning Algorithm

The multiplicity of design, construction, and use of IoT devices in homes has made it crucial to provide secure and manageable building management systems and platforms. Increasing security requires increasing the complexity of the user interface and the access verification steps in the system. Today, multi-step verification methods are used via SMS, call, or e-mail to do this. Another topic mentioned here is physical home security and energy management. Artificial intelligence and machine learning-based tools and algorithms are used to analyze images and data from sensors and security cameras. However, these tools are not always available due to the increase in data volume over time and the need for large processing resources. In this study, a new method is proposed to reduce the usage of process resources and the percentage of system error in anomaly detection by reducing visual data to critical points by using thermal cameras. This method can also be used in energy management using home and ambient temperature and user activity measurements. The statistical results of the visual comparison between the proposed method and the legacy CCTV-based visual and sensory surveillance shown in the results section demonstrate its reliability and accuracy

Time Series Forecasting for Retail Sales: A Comparative Study of Traditional Econometric Models and a Machine Learning Approach

openThis thesis compares the forecasting performances of FBProphet, Holt Winters' Exponential Smoothing, and Box Jenkins ARIMA models for retail sales in the US. Mean Absolute Percentage Error (MAPE) is used as the evaluation metric for comparing the forecasts in two different scenarios. The study aims to assess if FBProphet outperforms traditional econometric models in terms of forecasting accuracy. The findings shed light on the relative strengths and weaknesses of these models and contribute to improving retail sales forecasting methodologies

Innovation Agents

The standard narrative of entrepreneurship is one of self-employed creative individuals working out of their garage or independently owned start-up companies. Intrapreneurship--where employees are responsible for being alert to new opportunities inside firms--is another model for developing innovations. Relatively little is known, however, about the latter process through which large, complex firms engage in groundbreaking corporate entrepreneurship. This Article\u27s focus is on these types of innovation agents. It provides a thorough account of the positive and negative spillovers of intrapreneurial firms while making the following key points: First, intrapreneurial companies utilize their economies of scale, scope, and age to deliver innovations to the masses. They transform ideas, labor, and raw materials into tangible assets that can be traded in the market. Second, in doing so they offer individual entrepreneurs opportunities to capitalize their knowledge. Sustaining entrepreneurs\u27 prospects for supra-competitive profits is the main engine that motivates the latter to invest in discoveries in the first place. Lastly, intrapreneurial firms also serve as greenhouses for entrepreneurship through the migration of their own talented labor in the market. While these spillovers have tremendous societal benefits, they can also introduce harms. First, the race for the next breakthrough might result in anticompetitive behavior by rivals who conspire with employees-intrapreneurs to leave their firms and take with them confidential information. Second, intrapreneurs often aspire to undertake their own independent journey. In so doing, they leave secure positions and high salaries while carrying valuable knowledge and expertise. This, in return, often prompts intrapreneurial firms to act opportunistically and lock-in or lock-out intrapreneurs in restrictive and wasteful arrangements. As a solution, this Article proposes ways law can balance the positive and negative spillovers of intrapreneurship and ways the tax system can help achieve such result

Covid-19: reinforcing the impact of Islamic banking through value-based intermediation

The novel Covid-19 pandemic has caused an unprecedented human crisis around the globe. The necessary actions implemented to contain the virus have sparked both economic and social downturn. It shows the fragility and unpreparedness of the economy to face such a pandemic. Significant weakening of economic conditions has escalated the pressure on households, businesses and financial markets. However, before the Covid-19 outbreak, Bank Negara Malaysia has taken a new initiative by introducing Value-Based Intermediation (VBI). VBI’s strategy opens up a new holistic layer for Islamic banks in providing the public at large with impactful and profitable services. This paper discusses VBI’s strategy and its potential application from the viewpoint of Sharīʽah. This paper also discusses Islamic banks' activities in implementing VBI as well as their response to the Covid-19 pandemic, based on qualitative inquiry. The paper concludes that VBI is a long journey that requires significant transformation of mindset among key stakeholders. As Covid-19 has adversely impacted communities in several ways, Islamic banks could empower communities through provision of financial solutions that create positive impact

Product/Brand co-creation methodology crossing marketing, design thinking, creativity and management: ideas(r)evolution

This thesis introduce a new innovation methodology called IDEAS(R)EVOLUTION that was developed according to an on-going experimental research project started in 2007. This new approach to innovation has initial based on Design thinking for innovation theory and practice. The concept of design thinking for innovation has received much attention in recent years. This innovation approach has climbed from the design and designers knowledge field towards other knowledge areas, mainly business management and marketing. Human centered approach, radical collaboration, creativity and breakthrough thinking are the main founding principles of Design thinking that were adapted by those knowledge areas due to their assertively and fitness to the business context and market complexity evolution. Also Open innovation, User-centered innovation and later on Living Labs models emerge as answers to the market and consumers pressure and desire for new products, new services or new business models. Innovation became the principal business management focus and strategic orientation. All this changes had an impact also in the marketing theory. It is possible now to have better strategies, communications plans and continuous dialogue systems with the target audience, incorporating their insights and promoting them to the main dissemination ambassadors of our innovations in the market. Drawing upon data from five case studies, the empirical findings in this dissertation suggest that companies need to shift from Design thinking for innovation approach to an holistic, multidimensional and integrated innovation system. The innovation context it is complex, companies need deeper systems then the success formulas that “commercial “Design thinking for innovation “preaches”. They need to learn how to change their organization culture, how to empower their workforce and collaborators, how to incorporate external stakeholders in their innovation processes, hoe to measure and create key performance indicators throughout the innovation process to give them better decision making data, how to integrate meaning and purpose in their innovation philosophy. Finally they need to understand that the strategic innovation effort it is not a “one shot” story it is about creating a continuous flow of interaction and dialogue with their clients within a “value creation chain“ mindset; RESUMO: Metodologia de co-criação de um produto/marca cruzando Marketing, Design Thinking, Criativity and Management - IDEAS(R)EVOLUTION. Esta dissertação apresenta uma nova metodologia de inovação chamada IDEAS(R)EVOLUTION, que foi desenvolvida segundo um projecto de investigação experimental contínuo que teve o seu início em 2007. Esta nova abordagem baseou-se, inicialmente, na teoria e na práctica do Design thinking para a inovação. Actualmente o conceito do Design Thinking para a inovação “saiu” do dominio da area de conhecimento do Design e dos Designers, tendo despertado muito interesse noutras áreas como a Gestão e o Marketing. Uma abordagem centrada na Pessoa, a colaboração radical, a criatividade e o pensamento disruptivo são principios fundadores do movimento do Design thinking que têm sido adaptados por essas novas áreas de conhecimento devido assertividade e adaptabilidade ao contexto dos negócios e à evolução e complexidade do Mercado. Também os modelos de Inovação Aberta, a inovação centrada no utilizador e mais tarde os Living Labs, emergem como possiveis soluções para o Mercado e para a pressão e desejo dos consumidores para novos productos, serviços ou modelos de negócio. A inovação passou a ser o principal foco e orientação estratégica na Gestão. Todas estas mudanças também tiveram impacto na teoria do Marketing. Hoje é possivel criar melhores estratégias, planos de comunicação e sistemas continuos de diálogo com o público alvo, incorporando os seus insights e promovendo os consumidores como embaixadores na disseminação da inovação das empresas no Mercado Os resultados empiricos desta tese, construídos com a informação obtida nos cinco casos realizados, sugerem que as empresas precisam de se re-orientar do paradigma do Design thinking para a inovação, para um sistema de inovação mais holistico, multidimensional e integrado. O contexto da Inovação é complexo, por isso as empresas precisam de sistemas mais profundos e não apenas de “fórmulas comerciais” como o Design thinking para a inovação advoga. As Empresas precisam de aprender como mudar a sua cultura organizacional, como capacitar sua força de trabalho e colaboradores, como incorporar os públicos externos no processo de inovação, como medir o processo de inovação criando indicadores chave de performance e obter dados para um tomada de decisão mais informada, como integrar significado e propósito na sua filosofia de inovação. Por fim, precisam de perceber que uma estratégia de inovação não passa por ter “sucesso uma vez”, mas sim por criar um fluxo contínuo de interação e diálogo com os seus clientes com uma mentalidade de “cadeia de criação de valor