Planning Support System Research Articles

Temporal Lobe Epilepsy Focus Detection Based on the Correlation Between Brain MR Images and EEG Recordings with a Decision Tree

Background/Objectives: In this study, a medical decision support system is presented to assist physicians in epileptic focus detection by correlating MRI and EEG data of temporal lobe epilepsy patients. Methods: By exploiting the asymmetry in the hippocampus in MRI images and using voxel-based morphometry analysis, gray matter reduction in the temporal and limbic lobes is detected, and epileptic focus prediction is realized. In addition, an epileptic focus is also determined by calculating the asymmetry score from EEG channels. Finally, epileptic focus detection was performed by associating MRI and EEG data with a decision tree. Results: The results obtained from the proposed algorithm provide 100% overlap with the physician’s finding on the EEG data. Conclusions: MRI and EEG correlation in epileptic focus detection was improved compared with physicians. The proposed algorithm can be used as a medical decision support system for epilepsy diagnosis, treatment, and surgery planning.

Actionable human–water system modelling under uncertainty

Abstract. This paper develops an actionable interdisciplinary model that quantifies and assesses uncertainties in water resource allocation under climate change. To achieve this objective, we develop an innovative socio-ecological grand ensemble that combines climate, hydrological, and microeconomic ensemble experiments with a widely used decision support system for water resource planning and management. Each system is populated with multiple models (multi-model), which we use to evaluate the impacts of multiple climate scenarios and policies (multi-scenario, multi-forcing) across systems so as to identify plausible futures where water management policies meet or miss their objectives and to explore potential tipping points. The application of the methods is exemplified by a study conducted in the Douro River basin (DRB), an agricultural basin located in central Spain. Our results show how marginal climate changes can trigger non-linear water allocation changes in the decision support systems (DSSs) and/or non-linear adaptive responses of irrigators to water shortages. For example, while some irrigators barely experience economic losses (average profit and employment fall by < 0.5 %) under mild water allocation reductions of 5 % or lower, profit and employment fall by up to 12 % (∼ 24 ×) when water allocation is reduced by 10 % or less (∼ 2×). This substantiates the relevance of informing the potential natural and socio-economic impacts of adaptation strategies and related uncertainties for identifying robust decisions.

The Role of Diversified Geo-Information Technologies in Urban Governance: A Literature Review

Global urbanization has made urban governance a crucial aspect of sustainable urban development. While geo-information technologies have emerged as indispensable tools for effective urban governance, a comprehensive analysis of their application in this context remains lacking. This study seeks to review and assess the pivotal role of geo-information technologies in the field of urban governance. A total of 219 related studies were used for bibliometric analysis and key content analysis. Planning Support Systems (PSSs), Participatory Geographic Information Systems (PGISs), Building Information Modeling (BIM), and City Information Modeling (CIM) are identified as the main information technologies progressively employed across diverse stages of urban planning and construction over recent decades. These advancements have propelled the digital and intelligent management of urban areas, yielding significant benefits such as enhanced visualization, informed decision-making, and increased opportunities for citizen participation. However, a noticeable disparity between supply and demand during the application process arises from a lack of transdisciplinary cooperation. This study sheds light on the existing literature and offers policy implications and recommendations for more effective utilization of geo-information technologies in future spatial governance.

A Web-based decision support system for sustainable urban planning and management

Urban and territorial planning processes are characterized by a high level of complexity that makes tools management dif?cult. This research presents a Web-GIS prototype for supporting urban planning and management decision-making processes towards social, economic and environmental sustainability. It is designed according to open-source technology and aims to de?ne new planning top-down and bottom-up approaches. The design criteria of this innovative platform respond to the essential principles of transferability, modularity, scalability, and data interoperability. This new tool is applied to a case study to demonstrate how it can support planners and local authorities in urban planning and management processes.

Can we stop reinventing the wheel in blue-green infrastructure planning? Using value-focused thinking to enable transferability of a multicriteria planning support system

Strategic planning approaches are essential for addressing the complex and multi-dimensional challenges in selecting blue-green infrastructure (BGI) location. The development of planning support systems (PSS) for BGI siting often lacks a value-based approach with early stakeholder engagement. In this study, we used value-focused thinking (VFT) to adapt and develop a BGI planning support framework to the Canadian urban context, moving towards an objective-driven framework. We provide a hierarchical objectives framework for BGI planning in urban areas, aligned with stakeholder values, with three-level information: higher-level objectives, lower-level objectives and measurable spatial attributes. To assess site performance across these attributes, value scales elicitation was conducted with 17 experts. The engagement of 37 stakeholders in co-creating and validating our objectives set helped identify common concerns and refine our framework, focusing on the most relevant objectives for stakeholders. The VFT approach and the resulting framework can be easily transferred to other cities in Quebec (Canada), but also to other urban contexts looking to optimize BGI site selection to maximize benefits across the multiple functions of BGI and opportunities arising from the urban context.

Planning Support System Development for analysing environmental performance of form-based design decisions: Case Study of Enschede

Planning Support System Development for analysing environmental performance of form-based design decisions: Case Study of Enschede

Transitioning complex socioeconomic modeling to informed and visualized decision-making: A tightly coupled planning support system

The integration of urban models into decision-making remains challenging, primarily attributed to the complex nature of urban mechanisms. This study develops a PSS with sufficient methodological complexity to examine socioeconomic dynamics while simultaneously delivering modeling results in a manner that is understandable to non-expert stakeholders for informed decision-making. This paper tests, applies and implements the system in a real-life case at a fine scale collaborating with Sangamon County Regional Planning Commissions. It explores regional socioeconomic mechanisms across economic sectors addressing multicollinearity, projects potential consequences of an investment plan, and develops a web-based PSS tool for their informed decision-making. Our results identify how each economic sector behaves differently concerning location choices for future developments impacted by the investment, necessitating the use of differentiated planning approaches tailored to each sector. Findings underscore the value of assessing the heterogeneity of dynamic land development with spatial explicitness for informed decisions. We advocate for the delivery of this modeling via an interactive PSS platform, fostering responsive and collaborative dialogues. This paper contributes not only to the development of an integrated modeling framework but also to the planning literature, bridging the gap between complexity and accessibility in decision-making.

Integrating dynamic modeling and decision support systems for sustainable urban planning in a changing climate

ABSTRACT The study introduces the Ant Lion Recurrent Climate Estimation (ALRCE) model for precise climate forecasting, emphasizing critical parameters like rainfall, humidity, temperature, wind speed, and dew point. Its primary goal is to mitigate natural hazard risks stemming from sudden climate shifts. Data from Surat city, Gujarat, including these features, is meticulously processed to train the ALRCE model. It employs an ant lion fitness function for analysis, particularly predicting rainfall and drought rates. Implemented in MATLAB, it demonstrates superior precision, accuracy, and risk reduction, validated for future climatic predictions from 2025 to 2050. Comparative analysis with existing techniques shows ALRCE outperforms, achieving 96.5% accuracy, 98% precision, 0.18838 RMSE, and 0.63 correlation coefficient. The study enhances accuracy by 2% post-optimization, highlighting ALRCE’s potential to significantly improve climate prediction and mitigate risks associated with abrupt climate changes.

Coupling cellular automata and What If? models for residential expansion simulation: A case study of Southwest Sydney, Australia

AbstractThe impact of urban expansion on achieving sustainable development goals (SDGs) has become a significant research topic in the field of geographic information science. In this article, we describe a coupled cellular automata (CA)—‐What If? model to explore SDG11 “Sustainable cities and communities.” The model calculates overall residential land use demand based on historical data archives using the What If? planning support system (PSS), and then allocates it using a CA model that incorporates variables related to SDG11.2.1 and 11.7.1. Historical datasets for years 2016 and 2021 from Southwest Sydney, Australia were used to assess model accuracy, after which two residential expansion scenarios (years 2021 and 2026) were generated. Based on the modeling results, the SDG‐related spatial variables can improve the overall accuracy of CA sub‐models using an XGBoost machine learning training methodology. The simulation results of these scenarios confirm the effectiveness of the coupled CA‐What If? model, which has the potential to generate more reliable scenario results than the standalone What If? PSS for modeling urban growth of cities across Australia and internationally.

The Logistics of Volkswagen Development Center Applies Operations Research to Optimize Transshipments

Volkswagen Technical Development (TE) is responsible for all prototype development and prototype production for the Volkswagen brand and has its own logistics department (TE-Logistics). In the logistics of prototype parts in the automotive industry, new versions of prototype parts (henceforth referred to as updating parts) are repeatedly assembled in finished prototype vehicles. These updating parts are stored in warehouses and provided to an assembly site to ensure a timely assembly of the associated prototype vehicles. As the internal warehouse on the company site is not large enough for the high variety of parts, an additional external warehouse in the logistics network is needed. However, since prototype parts are unique, the allocation of the parts in suitable warehouses is particularly important. Currently, the various warehouses and the short-term demands repeatedly lead to reactive transshipments between the warehouses. To this end, we developed an approach for proactive transshipments based on a machine learning forecast and a mixed-integer linear programming model for planning proactive transshipments of parts between the warehouses to minimize transport costs. The model is based on a probability estimation of future demands to anticipate the expected optimal warehouse. After the model had revealed high improvement potential through a case study with real-world data in terms of costs and availability time compared to the current reactive process, we derived decision rules and developed a rule-based heuristic algorithm that leads to the optimal solution for the industrial use case. We implemented the heuristic with a spreadsheet-based decision support system (DSS) for daily transshipment planning. After successful test implementation, TE-Logistics estimated the annual cost savings for transport to be approximately 10%.

Implementation of Decision Support System for Ecological Environment Planning of Urban Green Space

Implementation of Decision Support System for Ecological Environment Planning of Urban Green Space

Agent-based decision-support model for bus route redesign in networks of small cities and towns: case study of Agder, Norway

Small cities and towns often struggle to provide high-quality public transport services to daily commuters. This is reflected in the modal split, where the share of car users dominates. Such a problem requires a modern solution, where transport planners can verify the impact of potential transport network improvements on the travel behavior of the residents before the changes are actually deployed. This study aims to demonstrate the usefulness of employing an agent-based simulation tool in the decision process for redesigning an express service regional bus route connecting a network of small cities and towns. The model was initially developed as a Mobility as a Service simulation solution for suburban areas of European metropolises. The model is adapted and applied to a case study for the region of Agder, Norway, simulating the impact of nine different scenarios on the patronage of a specific bus route. The simulation model proposes to upgrade the classic agent structure to a persona profile designed specifically for the case study. The main objective of this research is to identify the scenario that maximizes patronage while minimizing total route travel time and additional costs. The results suggest that the proposed model can be successfully adapted from suburban metropolitan areas to the realities of the considered case study, and potentially other similar regions. Specifically, out of the nine proposed scenarios, the model identified four promising ones. One of the four scenarios also fits the cost constraints imposed by the transport provider. The model provides a solid approach for analyzing complex transport systems that are practically impossible to consider in detail if the analysis is done without computer support. Thus, the results can be used as a decision support system for public transport planning and operations in networks of small cities and towns.

Development of planning support systems: A systematic review of the Chinese language literature

Due to the increasing complexity of cities and the involvement of multiple stakeholders in urban planning, the field encompasses vast amounts of information, expertise, planning tools, and communication skills. Planning support systems (PSS) are geo-information-technology-based instruments that offer a suite of supportive tools to aid the urban planning process. Over the past three decades, PSS has seen widespread exploration and implementation globally, including within the rapidly evolving context of China. Nonetheless, language barriers have posed challenges in reviewing and synthesizing PSS advancements documented in Chinese publications. To provide a thorough and objective perspective of the achievements in Chinese literature for international scholars, this study adopts a systematic review methodology. It screens 68 relevant high-quality articles from the China National Knowledge Infrastructure and conducts statistical analyses on them, focusing on publication time, geographic distribution, fields of study, etc. Then it mainly summarizes the development of foundational elements and the applications of the systems. It is found that in terms of system elements, China has developed some unique theories and corresponding planning models, alongside exploring various technological aspects. In applications, PSS serves various functions across different subfields, reflecting the division of labor in China’s planning process and the orientation of its policies. Future research avenues could encompass the creation of policy-driven comprehensive management functions, the development of systems tailored to specific contexts, and the exploration of new technologies like Information and Communication Technology (ICT) and generative Artificial Intelligence to boost PSS functionality and efficiency.

The Economic Impact of MIS Integration in Operations and Customer Relationship Management

This paper examines the strategic integration of Management Information Systems (MIS) within Operations Management (OM) and Customer Relationship Management (CRM) frameworks, emphasizing its pivotal role in bolstering economic efficiency. Through a synthesis of economic theories and MIS capabilities, the study delineates how this integration fosters improved operational processes, strategic decision-making, and customer engagement, thereby driving organizational economic benefits. Spanning process optimization, decision support systems, quality management, and customer relationship strategies, the analysis showcases the multifaceted economic impacts of MIS integration, including cost reduction, revenue enhancement, and customer satisfaction. By leveraging cutting-edge MIS technologies, organizations can harness data analytics to optimize processes, leverage decision support systems for strategic planning, implement quality management systems to uphold service standards, and personalize customer engagement to enhance satisfaction and loyalty. This study underscores the transformative potential of MIS in redefining operational efficiency and customer relationship strategies, providing valuable insights for businesses seeking to leverage technology for economic gain in the competitive market landscape.

A decision support system for localized planning of reclaimed water around wastewater treatment plants.

Exploding population, industrialization, and an increase in water pollution has led to acute shrinkage in freshwater availability. Numerous countries have started exploring municipal wastewater as a new potential source of water to bring a paradigm shift from linearity to obtaining circularity in human water cycle management. This study aims to develop a decision support system for integrated water and wastewater management (DSS_IWWM), targeted towards reuse-focused selection of appropriate wastewater treatment technology, and localized planning around STPs in terms of reclaimed water demand identification, estimation, allocation, and sustainable pricing. The developed DSS_IWWM comprises of a repository of fourteen reuse purposes, reuse quality criteria, and 25 wastewater treatment technologies (WWTTs) in 360 combinations. It is sensitive to local resource scenarios and applies a socioeconomic and technology-focused methodology for addressing the interests of the community and investing agencies and viably. To validate the application of the DSS_IWWM, it is first tested with data from three cities in the state of Uttar Pradesh (India)-Lucknow, Prayagraj, and Agra-and then extended to nine more Indian cities with varying influent quality characteristics, resource inputs, existing STP technologies, and same target quality and decision criteria prioritization, to present a comparison of appropriate WWTTs and associated average prices obtained in different scenarios. It is concluded that influent quality, existing technology, and target quality criteria play significant role in selection of appropriate WWTTs. The traditional technologies such as UASB and ASP are required to be augmented and supplemented with high-performing WWTTs, such as BIOFOR-F with (C + F + RSF) and SBT + WP to obtain desired effluent quality. High-performing advanced oxidation process (AOP)-based systems such as A2O, SBR, and BIOFOR-F require WWTTs with relatively lower average costs (such as SBT and OP). The developed DSS_IWWM may prove to be very useful and beneficial for policymakers, government officials, engineers, and scientific community as it will facilitate rational decision-making for efficient investment planning in reuse focused wastewater treatment towards achieving circular economy in sustainable water resource management.

A missed opportunity to implement a 3D digital twin in strategic planning in the Ålesund region, Norway: What to blame?

ABSTRACT While there have been academic discussions regarding the strategic and relational shift in spatial planning, and the potential of digital geospatial planning support systems (PSS) in this regard, the integration between these two has been given less attention. Understanding the obstacles associated with this integration is crucial to enhance strategic spatial planning and the utilization of geospatial PSS in this respect. To address this gap, the authors examine the tensions that arise when the planning systems of three municipalities in Norway intersect with the potential capabilities offered by a 3D digital twin. The authors found that the study findings not only supplemented those of studies concerned with the implementation gap, but also provided more general insights into possible obstacles for a strategic turn in spatial planning. In conclusion, they identify five key tensions in the Norwegian planning system that affect the uptake of a 3D digital twin.

Machine learning-based decision support system for orthognathic diagnosis and treatment planning

BackgroundDento-maxillofacial deformities are common problems. Orthodontic–orthognathic surgery is the primary treatment but accurate diagnosis and careful surgical planning are essential for optimum outcomes. This study aimed to establish and verify a machine learning–based decision support system for treatment of dento-maxillofacial malformations.MethodsPatients (n = 574) with dento-maxillofacial deformities undergoing spiral CT during January 2015 to August 2020 were enrolled to train diagnostic models based on five different machine learning algorithms; the diagnostic performances were compared with expert diagnoses. Accuracy, sensitivity, specificity, and area under the curve (AUC) were calculated. The adaptive artificial bee colony algorithm was employed to formulate the orthognathic surgical plan, and subsequently evaluated by maxillofacial surgeons in a cohort of 50 patients. The objective evaluation included the difference in bone position between the artificial intelligence (AI) generated and actual surgical plans for the patient, along with discrepancies in postoperative cephalometric analysis outcomes.ResultsThe binary relevance extreme gradient boosting model performed best, with diagnostic success rates > 90% for six different kinds of dento-maxillofacial deformities; the exception was maxillary overdevelopment (89.27%). AUC was > 0.88 for all diagnostic types. Median score for the surgical plans was 9, and was improved after human–computer interaction. There was no statistically significant difference between the actual and AI- groups.ConclusionsMachine learning algorithms are effective for diagnosis and surgical planning of dento-maxillofacial deformities and help improve diagnostic efficiency, especially in lower medical centers.

A Planning Support System for Monitoring Aging Neighborhoods in Germany

Many single-family homes built in Germany in the first decades following the Second World War are now occupied by elderly residents. If local conditions are unfavorable, a large number of these buildings may enter the real estate market in a short period of time and put pressure on the local housing market. Planners and decision-makers therefore need detailed spatiotemporal information about these neighborhoods to effectively address and counteract such developments. We present the design and implementation of a planning support system that can generate the required information. The architecture of this newly developed software consists of a composite, multitier framework to perform the complex tasks of data importation, data processing, and visualization. Legally mandated municipal population registers provide the key data for the calculation of indicators as a base for spatiotemporal analyses and visualizations. These registers offer high data quality in terms of completeness, logical consistency, spatial, and temporal and thematic accuracy. We demonstrate the implemented method using population data from a local government in a rural area in southwestern Germany. The results show that the new tool, which relies on open software components, is capable to identify and prioritize areas with particularly high levels of problem pressure. The tool can be used not only for analyses in a local context, but also at a regional level.

Auto-CA: Automated Cobb Angle Measurement Based on Vertebrae Detection for Assessment of Spinal Curvature Deformity.

An accurate identification and localization of vertebrae in X-ray images can assist doctors in measuring Cobb angles for treating patients with adolescent idiopathic scoliosis. It is useful for clinical decision support systems for diagnosis, surgery planning, and spinal health analysis. Currently, publicly available annotated datasets on spinal vertebrae are small, making deep-learning-based detection methods that are highly data-dependent less accurate. In this article, we propose an algorithm based on convolutional neural networks that can be trained to detect vertebrae from a small set of images. This method can display critical information on a patient's spine, display vertebrae and their labels on the thoracic and lumbar, calculate the Cobb angle, and evaluate the severity of spinal deformities. The proposed achieved an average accuracy of 0.958 and 0.962 for classifying spinal deformities (i.e., C-shaped, S-shaped type 1, and S-shaped type 2) and severity of Cobb angle (i.e., normal, mild, moderate, and severe), respectively. The Cobb angle measurement had a median difference of less than 5° from the ground-truth with SMAPE of 5.27% and an error on landmark detection of 19.73. In addition, Lenke classification is used to analyze spinal deformities as types A, B, and C, which have an average accuracy of 0.924. Physicians can use the proposed system in clinical practice by providing X-ray images via the user interface.

Embedding planning support systems in spatial planning practice: the role of drift in implementing the Spatial Development Framework methodology

ABSTRACT Planning Support Systems (PSS) research has explored ways to improve PSS use and embeddedness. However, there is little knowledge of how unplanned changes during implementation impact outcomes. This paper answers the question, ‘How can drift influence PSS implementation and use?’ It applies the concept of drift (changes in new technology, user behaviour, and/or existing practice during ICT implementation) to explain how PSS users (GIS specialists, planners) initiate unplanned changes during implementation and use. Following a qualitative approach, we investigate a PSS implementation case study in Rwanda – the Spatial Development Framework (SDF) methodology – to establish the role of drift in PSS use and embeddedness. Our study reveals that a) user understanding and perception of PSS can initiate drift during implementation and use, and b) drift can influence outcomes of PSS use or embeddedness. This study confirms the role of drift in PSS use and embeddedness in Rwanda’s spatial planning process.